Overview

Brought to you by YData

Dataset statistics

Number of variables129
Number of observations26208
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.0 MiB
Average record size in memory1.1 KiB

Variable types

DateTime1
Categorical128

Dataset

DescriptionSix-Month Monitoring Dataset from a 10-Turbine Onshore Wind Farm in Greece.
URLhttps://doi.org/10.5281/zenodo.14546479

Alerts

Gear Oil Temp. Avg. [°C] has constant value "0" Constant
Gear Bearing Temp. Avg. [°C] has constant value "0" Constant
Gear Oil TemperatureLevel2_3 Avg. [°C] has constant value "0" Constant
Ambient WindSpeed Estimated Avg. [m/s] has constant value "0" Constant
Grid Production PossibleInductive Avg. [var] has constant value "0" Constant
Grid Production PossibleInductive Max. [var] has constant value "0" Constant
Grid Production PossibleInductive Min. [var] has constant value "0" Constant
Grid Production PossibleInductive StdDev [var] has constant value "0" Constant
Grid Production PossibleCapacitive Avg. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Max. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Min. [var] has constant value "0" Constant
Grid Production PossibleCapacitive StdDev [var] has constant value "0" Constant
Active power limit source has constant value "0" Constant
Reactive power set point [var] has constant value "0" Constant
Power factor set point has constant value "0" Constant
Power factor set point source has constant value "0" Constant
Spinner Temp. SlipRing Avg. [°C] has constant value "0" Constant
HourCounters Average Total Avg. [h] has constant value "0" Constant
Total hour counter [h] has constant value "0" Constant
Grid on hours [h] has constant value "0" Constant
Grid ok hours [h] has constant value "0" Constant
Turbine ok hours [h] has constant value "0" Constant
Run hours [h] has constant value "0" Constant
Generator 1 hours [h] has constant value "0" Constant
Generator 2 hours [h] has constant value "0" Constant
Yaw hours [h] has constant value "0" Constant
Service hours [h] has constant value "0" Constant
Ambient ok hours [h] has constant value "0" Constant
Wind ok hours [h] has constant value "0" Constant
Active power generator 0, Total accumulated [W] has constant value "0" Constant
Active power generator 1, Total accumulated [W] has constant value "0" Constant
Reactive power generator 1, Total accumulated [var] has constant value "0" Constant
Reactive power generator 2, Total accumulated [var] has constant value "0" Constant
Blades PitchAngle Min. [°] is highly overall correlated with Blades PitchAngle StdDev [°] and 2 other fieldsHigh correlation
Blades PitchAngle StdDev [°] is highly overall correlated with Blades PitchAngle Min. [°]High correlation
Generator RPM Avg. [RPM] is highly overall correlated with Rotor RPM Avg. [RPM]High correlation
Generator RPM Max. [RPM] is highly overall correlated with Rotor RPM Max. [RPM]High correlation
Generator RPM Min. [RPM] is highly overall correlated with Rotor RPM Min. [RPM]High correlation
Generator RPM StdDev [RPM] is highly overall correlated with Rotor RPM StdDev [RPM]High correlation
Grid Production CurrentPhase1 Avg. [A] is highly overall correlated with Grid Production CurrentPhase2 Avg. [A] and 3 other fieldsHigh correlation
Grid Production CurrentPhase2 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 3 other fieldsHigh correlation
Grid Production CurrentPhase3 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Avg. [W] is highly overall correlated with Grid Production CurrentPhase3 Avg. [A] and 2 other fieldsHigh correlation
Grid Production PossiblePower Max. [W] is highly overall correlated with Grid Production Power Max. [W]High correlation
Grid Production PossiblePower Min. [W] is highly overall correlated with Grid Production Power Min. [W]High correlation
Grid Production PossiblePower StdDev [W] is highly overall correlated with Grid Production Power StdDev [W]High correlation
Grid Production Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production Power Max. [W] is highly overall correlated with Grid Production PossiblePower Max. [W]High correlation
Grid Production Power Min. [W] is highly overall correlated with Grid Production PossiblePower Min. [W]High correlation
Grid Production Power StdDev [W] is highly overall correlated with Grid Production PossiblePower StdDev [W]High correlation
Grid Production ReactivePower Avg. [W] is highly overall correlated with Blades PitchAngle Min. [°] and 5 other fieldsHigh correlation
Grid Production ReactivePower Max. [W] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 2 other fieldsHigh correlation
Grid Production ReactivePower Min. [W] is highly overall correlated with Grid Production ReactivePower Max. [W]High correlation
Grid Production VoltagePhase1 Avg. [V] is highly overall correlated with Grid Production VoltagePhase2 Avg. [V]High correlation
Grid Production VoltagePhase2 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V]High correlation
HourCounters Average AlarmActive Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average AmbientOk Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average Gen1 Avg. [h] is highly overall correlated with HourCounters Average Gen2 Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average Gen2 Avg. [h] is highly overall correlated with Blades PitchAngle Min. [°] and 6 other fieldsHigh correlation
HourCounters Average GridOk Avg. [h] is highly overall correlated with HourCounters Average GridOn Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average GridOn Avg. [h] is highly overall correlated with HourCounters Average GridOk Avg. [h]High correlation
HourCounters Average Run Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average TurbineOk Avg. [h] is highly overall correlated with HourCounters Average GridOk Avg. [h]High correlation
Production LatestAverage Active Power Gen 0 Avg. [W] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 2 other fieldsHigh correlation
Production LatestAverage Active Power Gen 1 Avg. [W] is highly overall correlated with HourCounters Average Gen1 Avg. [h]High correlation
Production LatestAverage Active Power Gen 2 Avg. [W] is highly overall correlated with HourCounters Average Gen2 Avg. [h]High correlation
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 3 other fieldsHigh correlation
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly overall correlated with Production LatestAverage Total Reactive Power Avg. [var]High correlation
Production LatestAverage Total Active Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Production LatestAverage Total Reactive Power Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 2 other fieldsHigh correlation
Rotor RPM Avg. [RPM] is highly overall correlated with Generator RPM Avg. [RPM]High correlation
Rotor RPM Max. [RPM] is highly overall correlated with Generator RPM Max. [RPM]High correlation
Rotor RPM Min. [RPM] is highly overall correlated with Generator RPM Min. [RPM]High correlation
Rotor RPM StdDev [RPM] is highly overall correlated with Generator RPM StdDev [RPM]High correlation
Generator RPM Max. [RPM] is highly imbalanced (63.9%) Imbalance
Generator RPM Min. [RPM] is highly imbalanced (56.0%) Imbalance
Generator RPM Avg. [RPM] is highly imbalanced (56.3%) Imbalance
Generator RPM StdDev [RPM] is highly imbalanced (57.8%) Imbalance
Generator Bearing Temp. Avg. [°C] is highly imbalanced (78.1%) Imbalance
Generator Phase1 Temp. Avg. [°C] is highly imbalanced (76.2%) Imbalance
Generator Phase2 Temp. Avg. [°C] is highly imbalanced (77.6%) Imbalance
Generator Phase3 Temp. Avg. [°C] is highly imbalanced (79.3%) Imbalance
Generator SlipRing Temp. Avg. [°C] is highly imbalanced (54.5%) Imbalance
Generator Bearing2 Temp. Avg. [°C] is highly imbalanced (77.2%) Imbalance
Hydraulic Oil Temp. Avg. [°C] is highly imbalanced (80.4%) Imbalance
Gear Oil TemperatureBasis Avg. [°C] is highly imbalanced (61.6%) Imbalance
Gear Bearing TemperatureHSRotorEnd Avg. [°C] is highly imbalanced (74.1%) Imbalance
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C] is highly imbalanced (68.1%) Imbalance
Gear Bearing TemperatureHSMiddle Avg. [°C] is highly imbalanced (65.8%) Imbalance
Gear Bearing TemperatureHollowShaftRotor Avg. [°C] is highly imbalanced (57.0%) Imbalance
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C] is highly imbalanced (61.1%) Imbalance
Rotor RPM Max. [RPM] is highly imbalanced (53.6%) Imbalance
Rotor RPM Avg. [RPM] is highly imbalanced (61.2%) Imbalance
Ambient WindSpeed Max. [m/s] is highly imbalanced (90.4%) Imbalance
Ambient WindSpeed Min. [m/s] is highly imbalanced (85.7%) Imbalance
Ambient WindSpeed Avg. [m/s] is highly imbalanced (91.3%) Imbalance
Ambient WindSpeed StdDev [m/s] is highly imbalanced (68.5%) Imbalance
Ambient WindDir Relative Avg. [°] is highly imbalanced (83.2%) Imbalance
Ambient WindDir Absolute Avg. [°] is highly imbalanced (84.7%) Imbalance
Grid InverterPhase1 Temp. Avg. [°C] is highly imbalanced (51.3%) Imbalance
Grid Production Power Avg. [W] is highly imbalanced (79.4%) Imbalance
Grid Production CosPhi Avg. is highly imbalanced (73.5%) Imbalance
Grid Production Frequency Avg. [Hz] is highly imbalanced (95.8%) Imbalance
Grid Production VoltagePhase1 Avg. [V] is highly imbalanced (91.4%) Imbalance
Grid Production VoltagePhase2 Avg. [V] is highly imbalanced (91.1%) Imbalance
Grid Production VoltagePhase3 Avg. [V] is highly imbalanced (87.5%) Imbalance
Grid Production CurrentPhase1 Avg. [A] is highly imbalanced (79.4%) Imbalance
Grid Production CurrentPhase2 Avg. [A] is highly imbalanced (78.4%) Imbalance
Grid Production CurrentPhase3 Avg. [A] is highly imbalanced (78.9%) Imbalance
Grid Production Power Max. [W] is highly imbalanced (73.1%) Imbalance
Grid Production Power Min. [W] is highly imbalanced (73.3%) Imbalance
Grid Busbar Temp. Avg. [°C] is highly imbalanced (50.6%) Imbalance
Grid Production Power StdDev [W] is highly imbalanced (76.4%) Imbalance
Grid Production ReactivePower Avg. [W] is highly imbalanced (65.9%) Imbalance
Grid Production ReactivePower Max. [W] is highly imbalanced (53.6%) Imbalance
Grid Production PossiblePower Avg. [W] is highly imbalanced (84.4%) Imbalance
Grid Production PossiblePower Max. [W] is highly imbalanced (78.1%) Imbalance
Grid Production PossiblePower Min. [W] is highly imbalanced (79.3%) Imbalance
Grid Production PossiblePower StdDev [W] is highly imbalanced (79.0%) Imbalance
Active power limit [W] is highly imbalanced (99.5%) Imbalance
Controller Ground Temp. Avg. [°C] is highly imbalanced (89.5%) Imbalance
Controller Top Temp. Avg. [°C] is highly imbalanced (66.1%) Imbalance
Controller Hub Temp. Avg. [°C] is highly imbalanced (72.5%) Imbalance
Controller VCP Temp. Avg. [°C] is highly imbalanced (60.7%) Imbalance
Controller VCP ChokecoilTemp. Avg. [°C] is highly imbalanced (79.1%) Imbalance
Spinner Temp. Avg. [°C] is highly imbalanced (64.5%) Imbalance
Blades PitchAngle Min. [°] is highly imbalanced (60.6%) Imbalance
Blades PitchAngle Max. [°] is highly imbalanced (54.1%) Imbalance
Blades PitchAngle Avg. [°] is highly imbalanced (58.5%) Imbalance
HVTrafo Phase1 Temp. Avg. [°C] is highly imbalanced (79.5%) Imbalance
HVTrafo Phase2 Temp. Avg. [°C] is highly imbalanced (74.5%) Imbalance
HVTrafo Phase3 Temp. Avg. [°C] is highly imbalanced (72.7%) Imbalance
HVTrafo AirOutlet Temp. Avg. [°C] is highly imbalanced (52.1%) Imbalance
HourCounters Average GridOn Avg. [h] is highly imbalanced (99.7%) Imbalance
HourCounters Average GridOk Avg. [h] is highly imbalanced (99.6%) Imbalance
HourCounters Average TurbineOk Avg. [h] is highly imbalanced (99.5%) Imbalance
HourCounters Average Run Avg. [h] is highly imbalanced (96.8%) Imbalance
HourCounters Average Gen1 Avg. [h] is highly imbalanced (82.9%) Imbalance
HourCounters Average Gen2 Avg. [h] is highly imbalanced (68.1%) Imbalance
HourCounters Average ServiceOn Avg. [h] is highly imbalanced (99.8%) Imbalance
HourCounters Average AmbientOk Avg. [h] is highly imbalanced (96.9%) Imbalance
HourCounters Average WindOk Avg. [h] is highly imbalanced (70.8%) Imbalance
HourCounters Average AlarmActive Avg. [h] is highly imbalanced (96.8%) Imbalance
Production LatestAverage Active Power Gen 0 Avg. [W] is highly imbalanced (76.0%) Imbalance
Production LatestAverage Active Power Gen 1 Avg. [W] is highly imbalanced (84.5%) Imbalance
Production LatestAverage Active Power Gen 2 Avg. [W] is highly imbalanced (76.9%) Imbalance
Production LatestAverage Total Active Power Avg. [W] is highly imbalanced (80.1%) Imbalance
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly imbalanced (73.4%) Imbalance
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly imbalanced (55.5%) Imbalance
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly imbalanced (61.1%) Imbalance
Active power generator 2, Total accumulated [W] is highly imbalanced (99.8%) Imbalance
Total Active power [W] is highly imbalanced (99.3%) Imbalance
Reactive power generator 0,Total accumulated [var] is highly imbalanced (99.9%) Imbalance
Total reactive power [var] is highly imbalanced (99.3%) Imbalance
Timestamp has unique values Unique

Reproduction

Analysis started2025-05-15 12:31:35.183462
Analysis finished2025-05-15 12:32:04.117078
Duration28.93 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Timestamp
Date

Unique 

Distinct26208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Minimum2020-01-01 00:00:00
Maximum2020-06-30 23:50:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-15T14:32:04.157186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-15T14:32:04.242105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Generator RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24407 
1
 
1801

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24407
93.1%
1 1801
 
6.9%

Length

2025-05-15T14:32:04.317202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:04.355021image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24407
93.1%
1 1801
 
6.9%

Most occurring characters

ValueCountFrequency (%)
0 24407
93.1%
1 1801
 
6.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24407
93.1%
1 1801
 
6.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24407
93.1%
1 1801
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24407
93.1%
1 1801
 
6.9%

Generator RPM Min. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23824 
1
2384 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23824
90.9%
1 2384
 
9.1%

Length

2025-05-15T14:32:04.397905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:04.434608image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23824
90.9%
1 2384
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 23824
90.9%
1 2384
 
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23824
90.9%
1 2384
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23824
90.9%
1 2384
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23824
90.9%
1 2384
 
9.1%

Generator RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23843 
1
 
2365

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23843
91.0%
1 2365
 
9.0%

Length

2025-05-15T14:32:04.480855image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:04.517743image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23843
91.0%
1 2365
 
9.0%

Most occurring characters

ValueCountFrequency (%)
0 23843
91.0%
1 2365
 
9.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23843
91.0%
1 2365
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23843
91.0%
1 2365
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23843
91.0%
1 2365
 
9.0%

Generator RPM StdDev [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23961 
1
 
2247

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23961
91.4%
1 2247
 
8.6%

Length

2025-05-15T14:32:04.562765image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:04.601589image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23961
91.4%
1 2247
 
8.6%

Most occurring characters

ValueCountFrequency (%)
0 23961
91.4%
1 2247
 
8.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23961
91.4%
1 2247
 
8.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23961
91.4%
1 2247
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23961
91.4%
1 2247
 
8.6%

Generator Bearing Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25291 
1
 
917

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25291
96.5%
1 917
 
3.5%

Length

2025-05-15T14:32:04.646653image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:04.683181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25291
96.5%
1 917
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 25291
96.5%
1 917
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25291
96.5%
1 917
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25291
96.5%
1 917
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25291
96.5%
1 917
 
3.5%

Generator Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25185 
1
 
1023

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25185
96.1%
1 1023
 
3.9%

Length

2025-05-15T14:32:04.728480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:04.764907image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25185
96.1%
1 1023
 
3.9%

Most occurring characters

ValueCountFrequency (%)
0 25185
96.1%
1 1023
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25185
96.1%
1 1023
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25185
96.1%
1 1023
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25185
96.1%
1 1023
 
3.9%

Generator Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25261 
1
 
947

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25261
96.4%
1 947
 
3.6%

Length

2025-05-15T14:32:04.809103image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:04.845245image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25261
96.4%
1 947
 
3.6%

Most occurring characters

ValueCountFrequency (%)
0 25261
96.4%
1 947
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25261
96.4%
1 947
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25261
96.4%
1 947
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25261
96.4%
1 947
 
3.6%

Generator Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25354 
1
 
854

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25354
96.7%
1 854
 
3.3%

Length

2025-05-15T14:32:04.887854image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:04.923990image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25354
96.7%
1 854
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25354
96.7%
1 854
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25354
96.7%
1 854
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25354
96.7%
1 854
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25354
96.7%
1 854
 
3.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23698 
1
2510 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23698
90.4%
1 2510
 
9.6%

Length

2025-05-15T14:32:04.968551image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:05.005668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23698
90.4%
1 2510
 
9.6%

Most occurring characters

ValueCountFrequency (%)
0 23698
90.4%
1 2510
 
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23698
90.4%
1 2510
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23698
90.4%
1 2510
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23698
90.4%
1 2510
 
9.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25243 
1
 
965

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25243
96.3%
1 965
 
3.7%

Length

2025-05-15T14:32:05.052632image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:05.089197image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25243
96.3%
1 965
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25243
96.3%
1 965
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25243
96.3%
1 965
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25243
96.3%
1 965
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25243
96.3%
1 965
 
3.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
21350 
1
4858 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21350
81.5%
1 4858
 
18.5%

Length

2025-05-15T14:32:05.131943image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:05.170457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 21350
81.5%
1 4858
 
18.5%

Most occurring characters

ValueCountFrequency (%)
0 21350
81.5%
1 4858
 
18.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 21350
81.5%
1 4858
 
18.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 21350
81.5%
1 4858
 
18.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 21350
81.5%
1 4858
 
18.5%

Hydraulic Oil Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25412 
1
 
796

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25412
97.0%
1 796
 
3.0%

Length

2025-05-15T14:32:05.215240image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:05.251692image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25412
97.0%
1 796
 
3.0%

Most occurring characters

ValueCountFrequency (%)
0 25412
97.0%
1 796
 
3.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25412
97.0%
1 796
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25412
97.0%
1 796
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25412
97.0%
1 796
 
3.0%

Gear Oil Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:05.296819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:05.330673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Gear Bearing Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:05.370529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:05.406369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24244 
1
 
1964

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24244
92.5%
1 1964
 
7.5%

Length

2025-05-15T14:32:05.446262image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:05.482522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24244
92.5%
1 1964
 
7.5%

Most occurring characters

ValueCountFrequency (%)
0 24244
92.5%
1 1964
 
7.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24244
92.5%
1 1964
 
7.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24244
92.5%
1 1964
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24244
92.5%
1 1964
 
7.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23131 
1
3077 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23131
88.3%
1 3077
 
11.7%

Length

2025-05-15T14:32:05.527387image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:05.564563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23131
88.3%
1 3077
 
11.7%

Most occurring characters

ValueCountFrequency (%)
0 23131
88.3%
1 3077
 
11.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23131
88.3%
1 3077
 
11.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23131
88.3%
1 3077
 
11.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23131
88.3%
1 3077
 
11.7%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:05.609601image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:05.645631image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25063 
1
 
1145

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25063
95.6%
1 1145
 
4.4%

Length

2025-05-15T14:32:05.685380image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:05.722431image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25063
95.6%
1 1145
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 25063
95.6%
1 1145
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25063
95.6%
1 1145
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25063
95.6%
1 1145
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25063
95.6%
1 1145
 
4.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24694 
1
 
1514

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24694
94.2%
1 1514
 
5.8%

Length

2025-05-15T14:32:05.918603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:05.954640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24694
94.2%
1 1514
 
5.8%

Most occurring characters

ValueCountFrequency (%)
0 24694
94.2%
1 1514
 
5.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24694
94.2%
1 1514
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24694
94.2%
1 1514
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24694
94.2%
1 1514
 
5.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24539 
1
 
1669

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24539
93.6%
1 1669
 
6.4%

Length

2025-05-15T14:32:05.997495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:06.035334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24539
93.6%
1 1669
 
6.4%

Most occurring characters

ValueCountFrequency (%)
0 24539
93.6%
1 1669
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24539
93.6%
1 1669
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24539
93.6%
1 1669
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24539
93.6%
1 1669
 
6.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23900 
1
 
2308

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23900
91.2%
1 2308
 
8.8%

Length

2025-05-15T14:32:06.077985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:06.114995image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23900
91.2%
1 2308
 
8.8%

Most occurring characters

ValueCountFrequency (%)
0 23900
91.2%
1 2308
 
8.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23900
91.2%
1 2308
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23900
91.2%
1 2308
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23900
91.2%
1 2308
 
8.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24209 
1
 
1999

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24209
92.4%
1 1999
 
7.6%

Length

2025-05-15T14:32:06.161223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:06.197516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24209
92.4%
1 1999
 
7.6%

Most occurring characters

ValueCountFrequency (%)
0 24209
92.4%
1 1999
 
7.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24209
92.4%
1 1999
 
7.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24209
92.4%
1 1999
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24209
92.4%
1 1999
 
7.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22934 
1
3274 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22934
87.5%
1 3274
 
12.5%

Length

2025-05-15T14:32:06.239825image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:06.278456image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22934
87.5%
1 3274
 
12.5%

Most occurring characters

ValueCountFrequency (%)
0 22934
87.5%
1 3274
 
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22934
87.5%
1 3274
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22934
87.5%
1 3274
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22934
87.5%
1 3274
 
12.5%

Rotor RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23625 
1
2583 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23625
90.1%
1 2583
 
9.9%

Length

2025-05-15T14:32:06.323207image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:06.360233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23625
90.1%
1 2583
 
9.9%

Most occurring characters

ValueCountFrequency (%)
0 23625
90.1%
1 2583
 
9.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23625
90.1%
1 2583
 
9.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23625
90.1%
1 2583
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23625
90.1%
1 2583
 
9.9%

Rotor RPM Min. [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23265 
1
2943 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23265
88.8%
1 2943
 
11.2%

Length

2025-05-15T14:32:06.407227image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:06.444211image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23265
88.8%
1 2943
 
11.2%

Most occurring characters

ValueCountFrequency (%)
0 23265
88.8%
1 2943
 
11.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23265
88.8%
1 2943
 
11.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23265
88.8%
1 2943
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23265
88.8%
1 2943
 
11.2%

Rotor RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24213 
1
 
1995

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24213
92.4%
1 1995
 
7.6%

Length

2025-05-15T14:32:06.490866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:06.527308image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24213
92.4%
1 1995
 
7.6%

Most occurring characters

ValueCountFrequency (%)
0 24213
92.4%
1 1995
 
7.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24213
92.4%
1 1995
 
7.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24213
92.4%
1 1995
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24213
92.4%
1 1995
 
7.6%

Rotor RPM StdDev [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23108 
1
3100 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23108
88.2%
1 3100
 
11.8%

Length

2025-05-15T14:32:06.570326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:06.609010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23108
88.2%
1 3100
 
11.8%

Most occurring characters

ValueCountFrequency (%)
0 23108
88.2%
1 3100
 
11.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23108
88.2%
1 3100
 
11.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23108
88.2%
1 3100
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23108
88.2%
1 3100
 
11.8%

Ambient WindSpeed Max. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25884 
1
 
324

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25884
98.8%
1 324
 
1.2%

Length

2025-05-15T14:32:06.653904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:06.690347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25884
98.8%
1 324
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 25884
98.8%
1 324
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25884
98.8%
1 324
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25884
98.8%
1 324
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25884
98.8%
1 324
 
1.2%

Ambient WindSpeed Min. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25675 
1
 
533

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25675
98.0%
1 533
 
2.0%

Length

2025-05-15T14:32:06.735826image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:06.772444image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25675
98.0%
1 533
 
2.0%

Most occurring characters

ValueCountFrequency (%)
0 25675
98.0%
1 533
 
2.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25675
98.0%
1 533
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25675
98.0%
1 533
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25675
98.0%
1 533
 
2.0%

Ambient WindSpeed Avg. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25923 
1
 
285

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25923
98.9%
1 285
 
1.1%

Length

2025-05-15T14:32:06.815419image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:06.853662image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25923
98.9%
1 285
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 25923
98.9%
1 285
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25923
98.9%
1 285
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25923
98.9%
1 285
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25923
98.9%
1 285
 
1.1%

Ambient WindSpeed StdDev [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24719 
1
 
1489

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24719
94.3%
1 1489
 
5.7%

Length

2025-05-15T14:32:06.897414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:06.933777image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24719
94.3%
1 1489
 
5.7%

Most occurring characters

ValueCountFrequency (%)
0 24719
94.3%
1 1489
 
5.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24719
94.3%
1 1489
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24719
94.3%
1 1489
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24719
94.3%
1 1489
 
5.7%

Ambient WindDir Relative Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25557 
1
 
651

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25557
97.5%
1 651
 
2.5%

Length

2025-05-15T14:32:06.979619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:07.016693image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25557
97.5%
1 651
 
2.5%

Most occurring characters

ValueCountFrequency (%)
0 25557
97.5%
1 651
 
2.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25557
97.5%
1 651
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25557
97.5%
1 651
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25557
97.5%
1 651
 
2.5%

Ambient WindDir Absolute Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25629 
1
 
579

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25629
97.8%
1 579
 
2.2%

Length

2025-05-15T14:32:07.059391image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:07.097964image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25629
97.8%
1 579
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 25629
97.8%
1 579
 
2.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25629
97.8%
1 579
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25629
97.8%
1 579
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25629
97.8%
1 579
 
2.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22427 
1
3781 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22427
85.6%
1 3781
 
14.4%

Length

2025-05-15T14:32:07.141354image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:07.178245image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22427
85.6%
1 3781
 
14.4%

Most occurring characters

ValueCountFrequency (%)
0 22427
85.6%
1 3781
 
14.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22427
85.6%
1 3781
 
14.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22427
85.6%
1 3781
 
14.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22427
85.6%
1 3781
 
14.4%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:07.225273image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:07.260561image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23439 
1
2769 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23439
89.4%
1 2769
 
10.6%

Length

2025-05-15T14:32:07.300867image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:07.339854image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23439
89.4%
1 2769
 
10.6%

Most occurring characters

ValueCountFrequency (%)
0 23439
89.4%
1 2769
 
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23439
89.4%
1 2769
 
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23439
89.4%
1 2769
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23439
89.4%
1 2769
 
10.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23003 
1
3205 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23003
87.8%
1 3205
 
12.2%

Length

2025-05-15T14:32:07.384617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:07.421822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23003
87.8%
1 3205
 
12.2%

Most occurring characters

ValueCountFrequency (%)
0 23003
87.8%
1 3205
 
12.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23003
87.8%
1 3205
 
12.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23003
87.8%
1 3205
 
12.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23003
87.8%
1 3205
 
12.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22983 
1
3225 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22983
87.7%
1 3225
 
12.3%

Length

2025-05-15T14:32:07.468673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:07.505711image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22983
87.7%
1 3225
 
12.3%

Most occurring characters

ValueCountFrequency (%)
0 22983
87.7%
1 3225
 
12.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22983
87.7%
1 3225
 
12.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22983
87.7%
1 3225
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22983
87.7%
1 3225
 
12.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22569 
1
3639 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22569
86.1%
1 3639
 
13.9%

Length

2025-05-15T14:32:07.550447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:07.589594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22569
86.1%
1 3639
 
13.9%

Most occurring characters

ValueCountFrequency (%)
0 22569
86.1%
1 3639
 
13.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22569
86.1%
1 3639
 
13.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22569
86.1%
1 3639
 
13.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22569
86.1%
1 3639
 
13.9%

Grid Production Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25360 
1
 
848

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25360
96.8%
1 848
 
3.2%

Length

2025-05-15T14:32:07.634553image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:07.671113image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25360
96.8%
1 848
 
3.2%

Most occurring characters

ValueCountFrequency (%)
0 25360
96.8%
1 848
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25360
96.8%
1 848
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25360
96.8%
1 848
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25360
96.8%
1 848
 
3.2%

Grid Production CosPhi Avg.
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25030 
1
 
1178

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25030
95.5%
1 1178
 
4.5%

Length

2025-05-15T14:32:07.722095image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:07.759428image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25030
95.5%
1 1178
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 25030
95.5%
1 1178
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25030
95.5%
1 1178
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25030
95.5%
1 1178
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25030
95.5%
1 1178
 
4.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26090 
1
 
118

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26090
99.5%
1 118
 
0.5%

Length

2025-05-15T14:32:07.802496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:07.840562image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26090
99.5%
1 118
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26090
99.5%
1 118
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26090
99.5%
1 118
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26090
99.5%
1 118
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26090
99.5%
1 118
 
0.5%

Grid Production VoltagePhase1 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25924 
1
 
284

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25924
98.9%
1 284
 
1.1%

Length

2025-05-15T14:32:07.883411image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:07.919951image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25924
98.9%
1 284
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 25924
98.9%
1 284
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25924
98.9%
1 284
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25924
98.9%
1 284
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25924
98.9%
1 284
 
1.1%

Grid Production VoltagePhase2 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25912 
1
 
296

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25912
98.9%
1 296
 
1.1%

Length

2025-05-15T14:32:07.964700image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:08.001044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25912
98.9%
1 296
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 25912
98.9%
1 296
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25912
98.9%
1 296
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25912
98.9%
1 296
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25912
98.9%
1 296
 
1.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25761 
1
 
447

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25761
98.3%
1 447
 
1.7%

Length

2025-05-15T14:32:08.043700image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:08.081712image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25761
98.3%
1 447
 
1.7%

Most occurring characters

ValueCountFrequency (%)
0 25761
98.3%
1 447
 
1.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25761
98.3%
1 447
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25761
98.3%
1 447
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25761
98.3%
1 447
 
1.7%

Grid Production CurrentPhase1 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25363 
1
 
845

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25363
96.8%
1 845
 
3.2%

Length

2025-05-15T14:32:08.124559image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:08.160918image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25363
96.8%
1 845
 
3.2%

Most occurring characters

ValueCountFrequency (%)
0 25363
96.8%
1 845
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25363
96.8%
1 845
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25363
96.8%
1 845
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25363
96.8%
1 845
 
3.2%

Grid Production CurrentPhase2 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25309 
1
 
899

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25309
96.6%
1 899
 
3.4%

Length

2025-05-15T14:32:08.205654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:08.241957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25309
96.6%
1 899
 
3.4%

Most occurring characters

ValueCountFrequency (%)
0 25309
96.6%
1 899
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25309
96.6%
1 899
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25309
96.6%
1 899
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25309
96.6%
1 899
 
3.4%

Grid Production CurrentPhase3 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25333 
1
 
875

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25333
96.7%
1 875
 
3.3%

Length

2025-05-15T14:32:08.284963image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:08.322828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25333
96.7%
1 875
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25333
96.7%
1 875
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25333
96.7%
1 875
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25333
96.7%
1 875
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25333
96.7%
1 875
 
3.3%

Grid Production Power Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25003 
1
 
1205

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25003
95.4%
1 1205
 
4.6%

Length

2025-05-15T14:32:08.365739image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:08.403212image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25003
95.4%
1 1205
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 25003
95.4%
1 1205
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25003
95.4%
1 1205
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25003
95.4%
1 1205
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25003
95.4%
1 1205
 
4.6%

Grid Production Power Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25014 
1
 
1194

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25014
95.4%
1 1194
 
4.6%

Length

2025-05-15T14:32:08.447932image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:08.484299image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25014
95.4%
1 1194
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 25014
95.4%
1 1194
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25014
95.4%
1 1194
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25014
95.4%
1 1194
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25014
95.4%
1 1194
 
4.6%

Grid Busbar Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23380 
1
2828 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23380
89.2%
1 2828
 
10.8%

Length

2025-05-15T14:32:08.527155image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:08.566112image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23380
89.2%
1 2828
 
10.8%

Most occurring characters

ValueCountFrequency (%)
0 23380
89.2%
1 2828
 
10.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23380
89.2%
1 2828
 
10.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23380
89.2%
1 2828
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23380
89.2%
1 2828
 
10.8%

Grid Production Power StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25197 
1
 
1011

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Length

2025-05-15T14:32:08.611346image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:08.647844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Most occurring characters

ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Grid Production ReactivePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24548 
1
 
1660

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24548
93.7%
1 1660
 
6.3%

Length

2025-05-15T14:32:08.693307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:08.730479image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24548
93.7%
1 1660
 
6.3%

Most occurring characters

ValueCountFrequency (%)
0 24548
93.7%
1 1660
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24548
93.7%
1 1660
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24548
93.7%
1 1660
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24548
93.7%
1 1660
 
6.3%

Grid Production ReactivePower Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23631 
1
2577 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23631
90.2%
1 2577
 
9.8%

Length

2025-05-15T14:32:08.774083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:08.965336image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23631
90.2%
1 2577
 
9.8%

Most occurring characters

ValueCountFrequency (%)
0 23631
90.2%
1 2577
 
9.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23631
90.2%
1 2577
 
9.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23631
90.2%
1 2577
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23631
90.2%
1 2577
 
9.8%

Grid Production ReactivePower Min. [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23300 
1
2908 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23300
88.9%
1 2908
 
11.1%

Length

2025-05-15T14:32:09.010557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:09.047461image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23300
88.9%
1 2908
 
11.1%

Most occurring characters

ValueCountFrequency (%)
0 23300
88.9%
1 2908
 
11.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23300
88.9%
1 2908
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23300
88.9%
1 2908
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23300
88.9%
1 2908
 
11.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22128 
1
4080 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22128
84.4%
1 4080
 
15.6%

Length

2025-05-15T14:32:09.093738image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:09.130715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22128
84.4%
1 4080
 
15.6%

Most occurring characters

ValueCountFrequency (%)
0 22128
84.4%
1 4080
 
15.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22128
84.4%
1 4080
 
15.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22128
84.4%
1 4080
 
15.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22128
84.4%
1 4080
 
15.6%

Grid Production PossiblePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25614 
1
 
594

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25614
97.7%
1 594
 
2.3%

Length

2025-05-15T14:32:09.175727image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:09.213799image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25614
97.7%
1 594
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 25614
97.7%
1 594
 
2.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25614
97.7%
1 594
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25614
97.7%
1 594
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25614
97.7%
1 594
 
2.3%

Grid Production PossiblePower Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25290 
1
 
918

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25290
96.5%
1 918
 
3.5%

Length

2025-05-15T14:32:09.256637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:09.292856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25290
96.5%
1 918
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 25290
96.5%
1 918
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25290
96.5%
1 918
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25290
96.5%
1 918
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25290
96.5%
1 918
 
3.5%

Grid Production PossiblePower Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25354 
1
 
854

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25354
96.7%
1 854
 
3.3%

Length

2025-05-15T14:32:09.337414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:09.373713image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25354
96.7%
1 854
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25354
96.7%
1 854
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25354
96.7%
1 854
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25354
96.7%
1 854
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25354
96.7%
1 854
 
3.3%

Grid Production PossiblePower StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25337 
1
 
871

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25337
96.7%
1 871
 
3.3%

Length

2025-05-15T14:32:09.418245image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:09.454817image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25337
96.7%
1 871
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25337
96.7%
1 871
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25337
96.7%
1 871
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25337
96.7%
1 871
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25337
96.7%
1 871
 
3.3%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:09.498257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:09.531929image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:09.574455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:09.608548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:09.651266image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:09.685501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:09.726140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:09.762283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:09.802732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:09.836866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:09.878829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:09.913486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:09.953444image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:09.989381image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:10.029745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:10.063894image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Active power limit [W]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26197 
1
 
11

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26197
> 99.9%
1 11
 
< 0.1%

Length

2025-05-15T14:32:10.105829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:10.142386image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26197
> 99.9%
1 11
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26197
> 99.9%
1 11
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26197
> 99.9%
1 11
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26197
> 99.9%
1 11
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26197
> 99.9%
1 11
 
< 0.1%

Active power limit source
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:10.185065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:10.221005image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Reactive power set point [var]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:10.261335image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:10.295231image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Power factor set point
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:10.337093image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:10.371239image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Power factor set point source
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:10.418981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:10.455116image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Controller Ground Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25848 
1
 
360

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25848
98.6%
1 360
 
1.4%

Length

2025-05-15T14:32:10.495035image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:10.531328image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25848
98.6%
1 360
 
1.4%

Most occurring characters

ValueCountFrequency (%)
0 25848
98.6%
1 360
 
1.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25848
98.6%
1 360
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25848
98.6%
1 360
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25848
98.6%
1 360
 
1.4%

Controller Top Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24557 
1
 
1651

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24557
93.7%
1 1651
 
6.3%

Length

2025-05-15T14:32:10.576420image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:10.612842image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24557
93.7%
1 1651
 
6.3%

Most occurring characters

ValueCountFrequency (%)
0 24557
93.7%
1 1651
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24557
93.7%
1 1651
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24557
93.7%
1 1651
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24557
93.7%
1 1651
 
6.3%

Controller Hub Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24970 
1
 
1238

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24970
95.3%
1 1238
 
4.7%

Length

2025-05-15T14:32:10.655755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:10.694071image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24970
95.3%
1 1238
 
4.7%

Most occurring characters

ValueCountFrequency (%)
0 24970
95.3%
1 1238
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24970
95.3%
1 1238
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24970
95.3%
1 1238
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24970
95.3%
1 1238
 
4.7%

Controller VCP Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24178 
1
 
2030

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24178
92.3%
1 2030
 
7.7%

Length

2025-05-15T14:32:10.737531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:10.774513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24178
92.3%
1 2030
 
7.7%

Most occurring characters

ValueCountFrequency (%)
0 24178
92.3%
1 2030
 
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24178
92.3%
1 2030
 
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24178
92.3%
1 2030
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24178
92.3%
1 2030
 
7.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25347 
1
 
861

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25347
96.7%
1 861
 
3.3%

Length

2025-05-15T14:32:10.819504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:10.856144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25347
96.7%
1 861
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25347
96.7%
1 861
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25347
96.7%
1 861
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25347
96.7%
1 861
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25347
96.7%
1 861
 
3.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22152 
1
4056 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22152
84.5%
1 4056
 
15.5%

Length

2025-05-15T14:32:10.899204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:10.938848image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22152
84.5%
1 4056
 
15.5%

Most occurring characters

ValueCountFrequency (%)
0 22152
84.5%
1 4056
 
15.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22152
84.5%
1 4056
 
15.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22152
84.5%
1 4056
 
15.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22152
84.5%
1 4056
 
15.5%

Spinner Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24450 
1
 
1758

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24450
93.3%
1 1758
 
6.7%

Length

2025-05-15T14:32:10.983998image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:11.020770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24450
93.3%
1 1758
 
6.7%

Most occurring characters

ValueCountFrequency (%)
0 24450
93.3%
1 1758
 
6.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24450
93.3%
1 1758
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24450
93.3%
1 1758
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24450
93.3%
1 1758
 
6.7%

Spinner Temp. SlipRing Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:11.065674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:11.099727image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Blades PitchAngle Min. [°]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24174 
1
 
2034

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24174
92.2%
1 2034
 
7.8%

Length

2025-05-15T14:32:11.139987image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:11.178261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24174
92.2%
1 2034
 
7.8%

Most occurring characters

ValueCountFrequency (%)
0 24174
92.2%
1 2034
 
7.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24174
92.2%
1 2034
 
7.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24174
92.2%
1 2034
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24174
92.2%
1 2034
 
7.8%

Blades PitchAngle Max. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23672 
1
2536 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23672
90.3%
1 2536
 
9.7%

Length

2025-05-15T14:32:11.221418image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:11.258705image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23672
90.3%
1 2536
 
9.7%

Most occurring characters

ValueCountFrequency (%)
0 23672
90.3%
1 2536
 
9.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23672
90.3%
1 2536
 
9.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23672
90.3%
1 2536
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23672
90.3%
1 2536
 
9.7%

Blades PitchAngle Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24015 
1
 
2193

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24015
91.6%
1 2193
 
8.4%

Length

2025-05-15T14:32:11.305369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:11.342576image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24015
91.6%
1 2193
 
8.4%

Most occurring characters

ValueCountFrequency (%)
0 24015
91.6%
1 2193
 
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24015
91.6%
1 2193
 
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24015
91.6%
1 2193
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24015
91.6%
1 2193
 
8.4%

Blades PitchAngle StdDev [°]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23230 
1
2978 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23230
88.6%
1 2978
 
11.4%

Length

2025-05-15T14:32:11.387752image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:11.426782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23230
88.6%
1 2978
 
11.4%

Most occurring characters

ValueCountFrequency (%)
0 23230
88.6%
1 2978
 
11.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23230
88.6%
1 2978
 
11.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23230
88.6%
1 2978
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23230
88.6%
1 2978
 
11.4%

HVTrafo Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25366 
1
 
842

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25366
96.8%
1 842
 
3.2%

Length

2025-05-15T14:32:11.472625image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:11.509075image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25366
96.8%
1 842
 
3.2%

Most occurring characters

ValueCountFrequency (%)
0 25366
96.8%
1 842
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25366
96.8%
1 842
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25366
96.8%
1 842
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25366
96.8%
1 842
 
3.2%

HVTrafo Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25088 
1
 
1120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25088
95.7%
1 1120
 
4.3%

Length

2025-05-15T14:32:11.554088image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:11.591086image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25088
95.7%
1 1120
 
4.3%

Most occurring characters

ValueCountFrequency (%)
0 25088
95.7%
1 1120
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25088
95.7%
1 1120
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25088
95.7%
1 1120
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25088
95.7%
1 1120
 
4.3%

HVTrafo Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24982 
1
 
1226

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24982
95.3%
1 1226
 
4.7%

Length

2025-05-15T14:32:11.634508image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:11.672675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24982
95.3%
1 1226
 
4.7%

Most occurring characters

ValueCountFrequency (%)
0 24982
95.3%
1 1226
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24982
95.3%
1 1226
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24982
95.3%
1 1226
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24982
95.3%
1 1226
 
4.7%

HVTrafo AirOutlet Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23504 
1
2704 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23504
89.7%
1 2704
 
10.3%

Length

2025-05-15T14:32:11.716277image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:11.754052image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23504
89.7%
1 2704
 
10.3%

Most occurring characters

ValueCountFrequency (%)
0 23504
89.7%
1 2704
 
10.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23504
89.7%
1 2704
 
10.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23504
89.7%
1 2704
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23504
89.7%
1 2704
 
10.3%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:11.801849image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:11.835717image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

HourCounters Average GridOn Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26203 
1
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26203
> 99.9%
1 5
 
< 0.1%

Length

2025-05-15T14:32:11.875915image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:11.914414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26203
> 99.9%
1 5
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26203
> 99.9%
1 5
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26203
> 99.9%
1 5
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26203
> 99.9%
1 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26203
> 99.9%
1 5
 
< 0.1%

HourCounters Average GridOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26201 
1
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Length

2025-05-15T14:32:12.112885image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:12.148997image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

HourCounters Average TurbineOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26197 
1
 
11

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26197
> 99.9%
1 11
 
< 0.1%

Length

2025-05-15T14:32:12.193298image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:12.229799image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26197
> 99.9%
1 11
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26197
> 99.9%
1 11
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26197
> 99.9%
1 11
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26197
> 99.9%
1 11
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26197
> 99.9%
1 11
 
< 0.1%

HourCounters Average Run Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26121 
1
 
87

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26121
99.7%
1 87
 
0.3%

Length

2025-05-15T14:32:12.272417image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:12.310556image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26121
99.7%
1 87
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 26121
99.7%
1 87
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26121
99.7%
1 87
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26121
99.7%
1 87
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26121
99.7%
1 87
 
0.3%

HourCounters Average Gen1 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25542 
1
 
666

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25542
97.5%
1 666
 
2.5%

Length

2025-05-15T14:32:12.353712image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:12.389962image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25542
97.5%
1 666
 
2.5%

Most occurring characters

ValueCountFrequency (%)
0 25542
97.5%
1 666
 
2.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25542
97.5%
1 666
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25542
97.5%
1 666
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25542
97.5%
1 666
 
2.5%

HourCounters Average Gen2 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24690 
1
 
1518

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24690
94.2%
1 1518
 
5.8%

Length

2025-05-15T14:32:12.434574image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:12.471228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24690
94.2%
1 1518
 
5.8%

Most occurring characters

ValueCountFrequency (%)
0 24690
94.2%
1 1518
 
5.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24690
94.2%
1 1518
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24690
94.2%
1 1518
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24690
94.2%
1 1518
 
5.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23008 
1
3200 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23008
87.8%
1 3200
 
12.2%

Length

2025-05-15T14:32:12.514800image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:12.553667image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23008
87.8%
1 3200
 
12.2%

Most occurring characters

ValueCountFrequency (%)
0 23008
87.8%
1 3200
 
12.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23008
87.8%
1 3200
 
12.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23008
87.8%
1 3200
 
12.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23008
87.8%
1 3200
 
12.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26204 
1
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Length

2025-05-15T14:32:12.599406image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:12.635595image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

HourCounters Average AmbientOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26126 
1
 
82

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26126
99.7%
1 82
 
0.3%

Length

2025-05-15T14:32:12.680563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:12.717387image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26126
99.7%
1 82
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 26126
99.7%
1 82
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26126
99.7%
1 82
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26126
99.7%
1 82
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26126
99.7%
1 82
 
0.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24861 
1
 
1347

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24861
94.9%
1 1347
 
5.1%

Length

2025-05-15T14:32:12.762505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:12.800091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24861
94.9%
1 1347
 
5.1%

Most occurring characters

ValueCountFrequency (%)
0 24861
94.9%
1 1347
 
5.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24861
94.9%
1 1347
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24861
94.9%
1 1347
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24861
94.9%
1 1347
 
5.1%

HourCounters Average AlarmActive Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26122 
1
 
86

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26122
99.7%
1 86
 
0.3%

Length

2025-05-15T14:32:12.842975image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:12.881253image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26122
99.7%
1 86
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 26122
99.7%
1 86
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26122
99.7%
1 86
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26122
99.7%
1 86
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26122
99.7%
1 86
 
0.3%

Total hour counter [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:12.924484image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:12.958599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid on hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:13.000650image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:13.034592image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:13.074379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:13.110161image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Turbine ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:13.150297image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:13.184316image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Run hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:13.226466image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:13.260428image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 1 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:13.300739image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:13.336439image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 2 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:13.376585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:13.410531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Yaw hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:13.452368image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:13.486665image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Service hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:13.526782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:13.562906image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Ambient ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:13.603548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:13.637787image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Wind ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:13.679908image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:13.714445image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Production LatestAverage Active Power Gen 0 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25172 
1
 
1036

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25172
96.0%
1 1036
 
4.0%

Length

2025-05-15T14:32:13.755445image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:13.794065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25172
96.0%
1 1036
 
4.0%

Most occurring characters

ValueCountFrequency (%)
0 25172
96.0%
1 1036
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25172
96.0%
1 1036
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25172
96.0%
1 1036
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25172
96.0%
1 1036
 
4.0%

Production LatestAverage Active Power Gen 1 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25620 
1
 
588

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25620
97.8%
1 588
 
2.2%

Length

2025-05-15T14:32:13.838071image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:13.874672image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25620
97.8%
1 588
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 25620
97.8%
1 588
 
2.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25620
97.8%
1 588
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25620
97.8%
1 588
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25620
97.8%
1 588
 
2.2%

Production LatestAverage Active Power Gen 2 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25226 
1
 
982

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Length

2025-05-15T14:32:13.920300image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:13.956850image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Production LatestAverage Total Active Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25399 
1
 
809

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25399
96.9%
1 809
 
3.1%

Length

2025-05-15T14:32:14.000502image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:14.039069image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25399
96.9%
1 809
 
3.1%

Most occurring characters

ValueCountFrequency (%)
0 25399
96.9%
1 809
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25399
96.9%
1 809
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25399
96.9%
1 809
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25399
96.9%
1 809
 
3.1%

Production LatestAverage Reactive Power Gen 0 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25022 
1
 
1186

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25022
95.5%
1 1186
 
4.5%

Length

2025-05-15T14:32:14.082299image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:14.119074image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25022
95.5%
1 1186
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 25022
95.5%
1 1186
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25022
95.5%
1 1186
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25022
95.5%
1 1186
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25022
95.5%
1 1186
 
4.5%

Production LatestAverage Reactive Power Gen 1 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23782 
1
2426 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23782
90.7%
1 2426
 
9.3%

Length

2025-05-15T14:32:14.163928image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:14.201151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23782
90.7%
1 2426
 
9.3%

Most occurring characters

ValueCountFrequency (%)
0 23782
90.7%
1 2426
 
9.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23782
90.7%
1 2426
 
9.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23782
90.7%
1 2426
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23782
90.7%
1 2426
 
9.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24210 
1
 
1998

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24210
92.4%
1 1998
 
7.6%

Length

2025-05-15T14:32:14.246109image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:14.284338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24210
92.4%
1 1998
 
7.6%

Most occurring characters

ValueCountFrequency (%)
0 24210
92.4%
1 1998
 
7.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24210
92.4%
1 1998
 
7.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24210
92.4%
1 1998
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24210
92.4%
1 1998
 
7.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22470 
1
3738 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22470
85.7%
1 3738
 
14.3%

Length

2025-05-15T14:32:14.327432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:14.364759image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22470
85.7%
1 3738
 
14.3%

Most occurring characters

ValueCountFrequency (%)
0 22470
85.7%
1 3738
 
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22470
85.7%
1 3738
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22470
85.7%
1 3738
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22470
85.7%
1 3738
 
14.3%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:14.411845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:14.445907image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:14.485888image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:14.521926image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26205 
1
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Length

2025-05-15T14:32:14.561940image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:14.599385image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Total Active power [W]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26194 
1
 
14

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26194
99.9%
1 14
 
0.1%

Length

2025-05-15T14:32:14.644911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:14.681545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26194
99.9%
1 14
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26194
99.9%
1 14
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26194
99.9%
1 14
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26194
99.9%
1 14
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26194
99.9%
1 14
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26207 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Length

2025-05-15T14:32:14.724947image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:14.763336image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:14.806668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:14.840986image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:32:14.882909image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:15.074458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Total reactive power [var]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26192 
1
 
16

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26192
99.9%
1 16
 
0.1%

Length

2025-05-15T14:32:15.114294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:32:15.151862image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26192
99.9%
1 16
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26192
99.9%
1 16
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26192
99.9%
1 16
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26192
99.9%
1 16
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26192
99.9%
1 16
 
0.1%

Correlations

2025-05-15T14:32:15.275778image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Active power generator 2, Total accumulated [W]Active power limit [W]Ambient Temp. Avg. [°C]Ambient WindDir Absolute Avg. [°]Ambient WindDir Relative Avg. [°]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed StdDev [m/s]Blades PitchAngle Avg. [°]Blades PitchAngle Max. [°]Blades PitchAngle Min. [°]Blades PitchAngle StdDev [°]Controller Ground Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Generator Bearing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator RPM Avg. [RPM]Generator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM StdDev [RPM]Generator SlipRing Temp. Avg. [°C]Grid Busbar Temp. Avg. [°C]Grid InverterPhase1 Temp. Avg. [°C]Grid Production CosPhi Avg.Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Frequency Avg. [Hz]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production Power Avg. [W]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HourCounters Average AlarmActive Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average Yaw Avg. [h]Hydraulic Oil Temp. Avg. [°C]Nacelle Temp. Avg. [°C]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Total Reactive Power Avg. [var]Reactive power generator 0,Total accumulated [var]Rotor RPM Avg. [RPM]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM StdDev [RPM]Spinner Temp. Avg. [°C]Total Active power [W]Total reactive power [var]
Active power generator 2, Total accumulated [W]1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0060.0000.0000.0000.0000.0000.0000.0000.0000.000
Active power limit [W]0.0001.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0240.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0000.0000.0000.0110.0140.0090.0220.0100.0000.0000.0000.0190.0000.0000.0000.0130.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0470.0480.0000.0000.1710.3370.0140.2260.0450.0050.0000.0000.0000.0080.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0110.0120.0000.000
Ambient Temp. Avg. [°C]0.0000.0001.0000.0000.0000.0160.0000.0150.0000.0300.0220.0290.0160.0090.0000.0080.0000.0380.0000.0110.0110.0040.0110.0060.0100.0230.0000.0000.0130.0050.0080.0000.0060.0000.0190.0000.0200.0380.0000.0000.0290.0200.0230.0000.0190.0040.0190.0200.0240.0040.0100.0170.0210.0190.0080.0200.0030.0000.0000.0000.0120.0050.0220.0220.0260.0060.0120.0070.0000.0080.0000.0000.0140.0000.0000.0000.0000.0050.1170.0230.0160.0000.0170.0090.0000.0270.0170.0000.0100.0000.0200.0000.0490.0000.000
Ambient WindDir Absolute Avg. [°]0.0000.0000.0001.0000.0720.0170.0050.0000.0190.0190.0160.0260.0060.0000.0150.0040.0000.0000.0000.0090.0210.0000.0090.0000.0000.0000.0110.0050.0040.0000.0020.0000.0080.0100.0140.0190.0130.0040.0000.0310.0220.0230.0260.0050.0130.0000.0110.0090.0110.0040.0000.0110.0280.0190.0270.0060.0090.0190.0000.0000.0060.0000.0090.0000.0000.0000.0040.0050.0000.0190.0000.0000.0040.0000.0000.0190.0290.0000.0100.0360.0070.0090.0280.0100.0080.0130.0020.0000.0160.0000.0060.0150.0030.0000.000
Ambient WindDir Relative Avg. [°]0.0000.0000.0000.0721.0000.0110.0250.0000.0200.0330.0940.0330.0130.0000.0310.0090.0180.0000.0140.0040.0000.0000.0050.0110.0000.0380.0150.0080.0060.0060.0050.0090.0250.0720.0290.0340.0170.0000.0000.0280.0070.0020.0080.0000.0000.0030.0000.0030.0000.0000.0000.0000.0560.0380.0290.0000.0060.0060.0000.0100.0120.0070.0060.0000.0000.0000.0570.0500.0000.0260.0000.0000.0570.0000.0000.0030.0220.0000.0130.0510.0030.0140.0620.0170.0100.0020.0210.0000.0350.0580.0200.0220.0150.0000.020
Ambient WindSpeed Avg. [m/s]0.0000.0000.0160.0170.0111.0000.1260.1010.0200.1270.0350.0760.0400.0040.0140.0000.0000.0040.0000.0640.0680.0540.0660.0770.0400.0000.0160.0080.0070.0380.0290.0250.1330.0870.0820.0640.0410.0380.0580.0270.2360.2220.2310.0030.2320.0950.0810.0530.2330.0900.0980.0540.0530.0370.0440.0400.0000.0050.0270.0290.0440.0310.0080.0000.0120.0000.0000.0000.0280.0560.0000.0000.0000.0000.0000.0380.0150.0000.0000.0550.1220.1020.0520.0000.0140.2290.0300.0000.1290.0690.0850.0610.0050.0000.000
Ambient WindSpeed Max. [m/s]0.0000.0000.0000.0050.0250.1261.0000.0230.0490.0740.0460.0700.0330.0000.0000.0110.0000.0000.0070.0290.0260.0250.0420.0380.0190.0000.0000.0000.0000.0240.0230.0240.0740.0790.0360.0250.0230.0200.0220.0360.1040.1140.1010.0000.0840.1130.0420.0690.1030.1060.0710.0640.0520.0480.0360.0400.0000.0000.0260.0180.0150.0160.0150.0000.0010.0120.0000.0000.0240.0490.0000.0000.0000.0000.0000.0460.0130.0000.0130.0540.0370.0600.0510.0080.0200.0970.0370.0000.0630.0710.0370.0260.0020.0000.000
Ambient WindSpeed Min. [m/s]0.0000.0160.0150.0000.0000.1010.0231.0000.0450.1010.0200.1450.1030.0090.0050.0000.0000.0000.0000.0320.0360.0330.0450.0340.0230.0000.0000.0110.0000.0320.0150.0190.0920.0540.1420.0840.0250.0290.0270.0630.0970.0830.1060.0000.0900.0480.1110.0550.1010.0450.1250.0600.0850.1020.1150.0860.0160.0010.0510.0310.0150.0150.0320.0090.0160.0150.0000.0000.0920.1130.0000.0270.0000.0070.0000.0500.0060.0000.0110.0640.0830.0820.0570.0310.0710.1000.0780.0000.0860.0400.1310.0570.0070.0000.000
Ambient WindSpeed StdDev [m/s]0.0000.0000.0000.0190.0200.0200.0490.0451.0000.0650.0000.0620.1020.0130.0340.0000.0000.0160.0000.0110.0020.0080.0090.0000.0000.0020.0000.0000.0000.0170.0150.0120.0410.0370.0090.0990.0000.0080.0160.0340.0330.0460.0390.0000.0260.0150.0450.1420.0320.0250.0310.1360.0230.0380.0260.0420.0000.0000.0000.0130.0100.0080.0210.0000.0110.0070.0000.0000.0140.0200.0000.0000.0000.0000.0000.0200.0510.0020.0030.0110.0170.0270.0100.0000.0280.0300.0120.0000.0370.0250.0070.0750.0120.0100.000
Blades PitchAngle Avg. [°]0.0000.0000.0300.0190.0330.1270.0740.1010.0651.0000.2130.4610.4420.0020.0210.0100.0100.0160.0170.0130.0350.0060.0780.0930.0150.0270.0130.0000.0060.0250.0170.0100.1800.1840.1720.1880.0500.0580.0510.2370.2000.1790.2060.0000.1590.1510.1670.2530.2080.1790.1620.2620.4060.3200.2180.2040.0000.0060.0360.0550.0490.0370.0000.0230.0140.0450.1430.1350.1730.3620.0050.0000.1390.0230.0160.1040.0770.0000.0170.2910.1060.2640.3140.1140.2470.2190.2930.0000.2040.1530.1400.1460.0110.0000.010
Blades PitchAngle Max. [°]0.0000.0000.0220.0160.0940.0350.0460.0200.0000.2131.0000.1250.0790.0030.0000.0070.0120.0120.0290.0280.0220.0000.0170.0680.0160.0570.0100.0200.0130.0110.0000.0000.0640.2100.0450.0430.0270.0000.0120.2440.1110.1030.1150.0100.0890.1180.0850.1560.1170.1320.0760.1180.1640.1630.0470.0600.0000.0040.0060.0150.0190.0140.0000.0230.0030.0020.0950.0890.0230.1690.0000.0000.0920.0000.0000.1750.0260.0130.0170.2090.0020.0970.2200.0360.0680.1230.0920.0000.0660.1850.0330.0470.0020.0000.000
Blades PitchAngle Min. [°]0.0000.0000.0290.0260.0330.0760.0700.1450.0620.4610.1251.0000.5560.0100.0150.0090.0090.0240.0090.0340.0530.0220.0590.0820.0130.0120.0000.0000.0070.0300.0160.0000.1820.1420.3010.2050.0410.0410.0380.2920.1710.1450.1720.0000.1320.1100.1370.2020.1890.1390.1400.2420.5780.4940.4140.3560.0080.0000.0570.0450.0350.0370.0000.0020.0150.0440.1370.1330.3020.5240.0160.0000.1360.0120.0170.1680.0410.0000.0070.4230.1890.2900.4040.1850.4310.1980.4290.0000.1940.1170.2490.1550.0080.0000.018
Blades PitchAngle StdDev [°]0.0110.0240.0160.0060.0130.0400.0330.1030.1020.4420.0790.5561.0000.0120.0280.0130.0060.0190.0100.0050.0240.0000.0400.0390.0090.0140.0000.0060.0000.0100.0160.0050.1340.1350.1920.3580.0300.0360.0260.2810.1370.1230.1400.0060.1350.1200.2390.2250.1650.1240.1920.2630.4580.3730.2840.3210.0000.0050.0320.0400.0280.0240.0040.0220.0140.0650.1190.1120.2310.4060.0270.0160.1160.0290.0180.1340.0930.0150.0030.3080.1380.2660.3140.1510.4730.1700.3310.0000.1480.1080.1470.2770.0180.0000.012
Controller Ground Temp. Avg. [°C]0.0000.0000.0090.0000.0000.0040.0000.0090.0130.0020.0030.0100.0121.0000.0080.0120.0100.0130.0000.0060.0140.0000.0000.0000.0000.0050.0000.0140.0100.0000.0000.0070.0000.0000.0000.0110.0000.0090.0050.0000.0070.0000.0050.0000.0000.0000.0100.0010.0070.0000.0050.0000.0060.0090.0000.0140.0000.0000.0000.0020.0000.0000.0000.0000.0000.0110.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0120.0070.0000.0000.0030.0040.0000.0000.0000.0050.0120.0000.0000.000
Controller Hub Temp. Avg. [°C]0.0000.0000.0000.0150.0310.0140.0000.0050.0340.0210.0000.0150.0280.0081.0000.0050.0080.0070.0000.0050.0050.0100.0050.0080.0080.0030.0030.0000.0000.0040.0000.0010.0080.0170.0200.0410.0030.0120.0000.0320.0480.0540.0530.0000.0180.0000.0340.0260.0390.0170.0440.0330.0440.0330.0260.0150.0130.0070.0110.0000.0000.0020.0050.0220.0130.0110.0190.0100.0000.0190.0000.0000.0160.0000.0060.0240.0120.0000.0150.0330.0000.0340.0400.0000.0160.0390.0190.0000.0170.0000.0090.0210.0500.0000.000
Controller Top Temp. Avg. [°C]0.0000.0000.0080.0040.0090.0000.0110.0000.0000.0100.0070.0090.0130.0120.0051.0000.0000.0240.0000.0050.0000.0000.0000.0060.0000.0190.0150.0260.0010.0000.0080.0180.0080.0000.0040.0080.0000.0170.0130.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0060.0000.0000.0000.0110.0100.0190.0360.0330.0270.0100.0000.0000.0170.0000.0000.0000.0000.0000.0000.0070.0000.0410.0470.0150.0170.0000.0160.0340.0080.0000.0230.0000.0040.0000.0080.0000.0270.0000.000
Controller VCP ChokecoilTemp. Avg. [°C]0.0000.0000.0000.0000.0180.0000.0000.0000.0000.0100.0120.0090.0060.0100.0080.0001.0000.0080.0000.0190.0350.0000.0050.0000.0390.0190.0270.0240.0100.0290.0630.0590.0150.0000.0000.0280.0060.0320.0280.0020.0000.0000.0040.0000.0150.0000.0110.0000.0000.0140.0000.0000.0000.0000.0040.0030.0000.0000.0000.0260.0270.0320.0130.0330.0400.0290.0060.0060.0160.0000.0000.0000.0060.0000.0000.0100.0000.0000.0000.0080.0040.0100.0110.0000.0000.0000.0000.0000.0080.0000.0000.0240.0000.0000.000
Controller VCP Temp. Avg. [°C]0.0000.0000.0380.0000.0000.0040.0000.0000.0160.0160.0120.0240.0190.0130.0070.0240.0081.0000.0030.0000.0000.0070.0230.0220.0000.0150.0170.0220.0150.0030.0210.0100.0000.0220.0140.0160.0510.0690.0090.0250.0180.0080.0140.0000.0050.0140.0240.0180.0160.0190.0200.0140.0220.0210.0140.0160.0230.0110.0160.0000.0170.0140.0550.0270.0500.0510.0110.0110.0000.0270.0000.0000.0110.0000.0000.0170.0100.0000.0780.0350.0000.0310.0300.0050.0220.0230.0110.0000.0030.0200.0030.0230.0140.0000.000
Controller VCP WaterTemp. Avg. [°C]0.0000.0000.0000.0000.0140.0000.0070.0000.0000.0170.0290.0090.0100.0000.0000.0000.0000.0031.0000.0360.0250.0090.0390.0350.0170.0000.0490.0180.2780.0590.0340.0500.0080.0000.0090.0080.0050.0310.1330.0000.0000.0050.0000.0080.0040.0130.0030.0130.0130.0060.0000.0180.0000.0000.0070.0120.0000.0010.0130.1920.2080.2140.0000.0140.0190.0140.0100.0090.0070.0000.0000.0000.0090.0000.0000.0000.0050.0000.0020.0020.0130.0000.0000.0240.0010.0150.0200.0000.0000.0050.0140.0060.0000.0000.000
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]0.0000.0000.0110.0090.0040.0640.0290.0320.0110.0130.0280.0340.0050.0060.0050.0050.0190.0000.0361.0000.2940.2190.1320.1630.1920.0050.0460.0800.0290.1120.0960.1020.1110.0430.0720.0560.0580.0250.0720.0500.0810.0760.0780.0000.0570.0500.0260.0220.0610.0400.0310.0200.0210.0290.0300.0400.0000.0000.0250.0540.0640.0380.0060.0100.0130.0000.0500.0490.0120.0150.0000.0000.0490.0000.0000.0450.0110.0000.0000.0510.0610.0100.0410.0060.0130.0650.0260.0000.0920.0520.0810.0570.0070.0000.000
Gear Bearing TemperatureHSMiddle Avg. [°C]0.0000.0000.0110.0210.0000.0680.0260.0360.0020.0350.0220.0530.0240.0140.0050.0000.0350.0000.0250.2941.0000.1000.1880.1850.2460.0290.0680.0930.0190.1200.1070.1240.1160.0570.0850.0520.0440.0480.0520.0420.0820.0830.0810.0070.0820.0400.0270.0370.0820.0420.0300.0390.0610.0430.0390.0430.0000.0050.0230.0600.0520.0600.0270.0190.0200.0260.0680.0700.0260.0510.0000.0000.0680.0000.0000.0460.0000.0000.0040.0800.0910.0000.0850.0000.0160.0840.0410.0000.1170.0580.1030.0490.0000.0000.000
Gear Bearing TemperatureHSRotorEnd Avg. [°C]0.0020.0000.0040.0000.0000.0540.0250.0330.0080.0060.0000.0220.0000.0000.0100.0000.0000.0070.0090.2190.1001.0000.1410.1150.1390.0000.0450.0430.0140.0800.0390.0330.1580.0480.0920.0830.0500.0090.0410.0040.0560.0520.0560.0000.0370.0550.0220.0280.0450.0520.0270.0320.0000.0430.0550.0460.0000.0050.0570.0500.0500.0430.0020.0050.0000.0000.0810.0760.0200.0070.0000.0000.0800.0000.0000.0000.0050.0120.0100.0230.0520.0040.0170.0260.0290.0570.0190.0000.1380.0670.0870.0720.0000.0000.000
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]0.0000.0000.0110.0090.0050.0660.0420.0450.0090.0780.0170.0590.0400.0000.0050.0000.0050.0230.0390.1320.1880.1411.0000.2330.2060.0150.0770.1130.0260.0780.0960.0750.1830.0430.1410.0900.0410.0490.0420.0250.0530.0440.0450.0000.0560.0670.0230.0530.0630.0540.0130.0480.0500.0640.0770.0850.0030.0000.0650.0440.0490.0470.0130.0000.0090.0150.0600.0570.0190.0480.0000.0000.0590.0000.0000.0000.0000.0050.0040.0750.0610.0000.0720.0260.0000.0670.0600.0000.1940.0510.1390.1010.0070.0000.000
Gear Bearing TemperatureHollowShaftRotor Avg. [°C]0.0000.0000.0060.0000.0110.0770.0380.0340.0000.0930.0680.0820.0390.0000.0080.0060.0000.0220.0350.1630.1850.1150.2331.0000.1600.0080.0640.0930.0200.0720.0680.0450.1980.0900.1220.0800.0660.0500.0350.0440.0720.0760.0770.0000.0660.0790.0410.0530.0680.0720.0230.0430.0750.0610.0530.0710.0000.0070.0560.0420.0540.0420.0000.0000.0050.0000.0510.0480.0170.0750.0000.0000.0510.0000.0000.0140.0000.0000.0020.1030.0530.0190.1050.0270.0000.0760.0790.0000.1980.1160.1300.0810.0000.0000.000
Gear Oil TemperatureBasis Avg. [°C]0.0000.0000.0100.0000.0000.0400.0190.0230.0000.0150.0160.0130.0090.0000.0080.0000.0390.0000.0170.1920.2460.1390.2060.1601.0000.0190.0860.1180.0280.1180.1310.1150.0940.0310.0670.0400.0360.0410.0390.0000.0170.0200.0160.0000.0200.0230.0030.0040.0140.0180.0000.0060.0100.0130.0170.0250.0110.0000.0280.0390.0330.0460.0080.0250.0120.0300.0250.0230.0150.0110.0000.0000.0240.0000.0000.0010.0000.0000.0150.0280.0370.0050.0270.0000.0000.0230.0140.0000.0940.0380.0720.0340.0040.0000.000
Gear Oil TemperatureLevel1 Avg. [°C]0.0000.0000.0230.0000.0380.0000.0000.0000.0020.0270.0570.0120.0140.0050.0030.0190.0190.0150.0000.0050.0290.0000.0150.0080.0191.0000.0080.0120.0170.0430.0440.0320.0190.0610.0300.0370.0000.0160.0000.0700.0070.0020.0000.0000.0000.0030.0160.0000.0000.0000.0040.0000.0540.0140.0070.0030.0070.0000.0090.0130.0000.0000.0000.0080.0440.0310.0310.0220.0000.0410.0000.0000.0310.0000.0000.0870.0160.0150.0490.0530.0000.0080.0670.0690.0460.0000.0110.0000.0300.0280.0310.0110.0360.0000.011
Generator Bearing Temp. Avg. [°C]0.0000.0000.0000.0110.0150.0160.0000.0000.0000.0130.0100.0000.0000.0000.0030.0150.0270.0170.0490.0460.0680.0450.0770.0640.0860.0081.0000.1890.0380.0930.0900.1050.0200.0090.0300.0000.0000.0540.0300.0060.0000.0070.0030.0000.0060.0000.0000.0000.0070.0000.0050.0000.0000.0000.0000.0110.0000.0000.0070.0330.0420.0490.0140.0500.0240.0460.0000.0000.0130.0070.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0060.0020.0000.0030.0000.0200.0230.0390.0000.0000.0000.000
Generator Bearing2 Temp. Avg. [°C]0.0000.0000.0000.0050.0080.0080.0000.0110.0000.0000.0200.0000.0060.0140.0000.0260.0240.0220.0180.0800.0930.0430.1130.0930.1180.0120.1891.0000.0250.1000.1010.1010.0370.0040.0170.0060.0070.0380.0140.0030.0060.0070.0170.0110.0000.0000.0070.0010.0000.0000.0000.0000.0000.0000.0080.0250.0000.0000.0050.0200.0310.0190.0150.0480.0330.0260.0000.0000.0080.0000.0000.0000.0000.0000.0000.0060.0060.0000.0170.0080.0160.0120.0000.0000.0110.0000.0000.0000.0430.0100.0300.0000.0090.0000.000
Generator CoolingWater Temp. Avg. [°C]0.0000.0040.0130.0040.0060.0070.0000.0000.0000.0060.0130.0070.0000.0100.0000.0010.0100.0150.2780.0290.0190.0140.0260.0200.0280.0170.0380.0251.0000.0480.0410.0330.0230.0070.0180.0000.0250.0190.1090.0080.0040.0040.0000.0050.0000.0110.0000.0000.0040.0020.0000.0000.0000.0120.0000.0000.0000.0000.0050.1420.1570.1550.0000.0250.0230.0220.0070.0000.0000.0130.0000.0000.0070.0000.0040.0130.0000.0040.0250.0170.0000.0000.0150.0000.0000.0050.0100.0000.0150.0230.0250.0000.0000.0000.008
Generator Phase1 Temp. Avg. [°C]0.0030.0000.0050.0000.0060.0380.0240.0320.0170.0250.0110.0300.0100.0000.0040.0000.0290.0030.0590.1120.1200.0800.0780.0720.1180.0430.0930.1000.0481.0000.4370.3410.0580.0290.0580.0360.0150.0400.0620.0450.0590.0560.0610.0000.0480.0300.0270.0280.0520.0450.0310.0280.0360.0320.0180.0180.0000.0000.0000.0840.0780.0840.0050.0210.0180.0400.0090.0100.0000.0230.0000.0000.0090.0000.0000.0410.0110.0000.0080.0480.0170.0110.0490.0290.0060.0500.0000.0000.0570.0150.0640.0260.0090.0000.000
Generator Phase2 Temp. Avg. [°C]0.0000.0000.0080.0020.0050.0290.0230.0150.0150.0170.0000.0160.0160.0000.0000.0080.0630.0210.0340.0960.1070.0390.0960.0680.1310.0440.0900.1010.0410.4371.0000.4770.0430.0250.0540.0210.0200.0360.0560.0310.0390.0300.0370.0000.0320.0210.0190.0170.0390.0360.0120.0170.0190.0190.0070.0190.0040.0000.0000.0590.0630.0500.0000.0430.0190.0520.0000.0000.0140.0140.0000.0000.0000.0000.0000.0160.0130.0150.0290.0360.0000.0000.0360.0380.0000.0340.0000.0000.0410.0180.0630.0110.0090.0000.000
Generator Phase3 Temp. Avg. [°C]0.0000.0000.0000.0000.0090.0250.0240.0190.0120.0100.0000.0000.0050.0070.0010.0180.0590.0100.0500.1020.1240.0330.0750.0450.1150.0320.1050.1010.0330.3410.4771.0000.0360.0040.0440.0180.0110.0480.0490.0240.0460.0300.0400.0000.0390.0400.0150.0200.0390.0470.0190.0170.0120.0110.0000.0190.0000.0000.0020.0660.0820.0580.0060.0460.0320.0280.0000.0000.0080.0000.0000.0000.0000.0000.0000.0170.0000.0000.0200.0220.0000.0000.0260.0260.0000.0340.0000.0000.0400.0000.0510.0120.0220.0000.000
Generator RPM Avg. [RPM]0.0000.0000.0060.0080.0250.1330.0740.0920.0410.1800.0640.1820.1340.0000.0080.0080.0150.0000.0080.1110.1160.1580.1830.1980.0940.0190.0200.0370.0230.0580.0430.0361.0000.3480.3790.4490.0330.0320.0160.1300.1720.1640.1740.0000.1290.1190.1100.1920.1670.1330.1010.1870.2130.1920.1930.1570.0080.0080.1010.0330.0400.0370.0040.0110.0000.0060.1390.1360.0460.1760.0140.0000.1380.0110.0150.0410.0420.0000.0000.2300.0550.1080.2610.0500.0810.1790.1810.0000.7380.3230.3550.3630.0000.0000.009
Generator RPM Max. [RPM]0.0000.0000.0000.0100.0720.0870.0790.0540.0370.1840.2100.1420.1350.0000.0170.0000.0000.0220.0000.0430.0570.0480.0430.0900.0310.0610.0090.0040.0070.0290.0250.0040.3481.0000.1120.2620.0240.0480.0100.1150.1460.1470.1490.0000.1070.1430.0960.1750.1270.1600.0930.1450.1680.1540.0690.0700.0040.0060.0270.0240.0050.0220.0000.0000.0000.0230.0960.0990.0850.1850.0070.0000.0960.0140.0000.0380.0250.0000.0000.1680.0160.1650.1900.0130.1030.1330.1070.0000.2900.7210.0980.1980.0230.0150.000
Generator RPM Min. [RPM]0.0000.0000.0190.0140.0290.0820.0360.1420.0090.1720.0450.3010.1920.0000.0200.0040.0000.0140.0090.0720.0850.0920.1410.1220.0670.0300.0300.0170.0180.0580.0540.0440.3790.1121.0000.2650.0450.0490.0460.1950.1360.1050.1310.0000.0810.0490.1410.0960.1470.0610.1620.1060.3110.2940.3370.2280.0140.0090.0920.0460.0410.0440.0000.0100.0230.0420.1080.1020.1640.3430.0000.0000.1070.0000.0000.1480.0270.0090.0060.3480.1360.1400.3370.0380.2110.1620.2340.0000.4070.1000.7740.2120.0000.0030.032
Generator RPM StdDev [RPM]0.0000.0160.0000.0190.0340.0640.0250.0840.0990.1880.0430.2050.3580.0110.0410.0080.0280.0160.0080.0560.0520.0830.0900.0800.0400.0370.0000.0060.0000.0360.0210.0180.4490.2620.2651.0000.0290.0110.0140.2180.1430.1420.1510.0000.1200.1260.2250.2390.1510.1420.2030.2550.2040.1970.1900.2410.0130.0070.0480.0260.0200.0190.0000.0000.0070.0330.0950.0910.0070.1910.0150.0000.0950.0110.0160.0710.1040.0040.0000.2200.0100.1510.2460.0080.2790.1600.1380.0000.4230.2200.2400.6620.0140.0120.016
Generator SlipRing Temp. Avg. [°C]0.0000.0000.0200.0130.0170.0410.0230.0250.0000.0500.0270.0410.0300.0000.0030.0000.0060.0510.0050.0580.0440.0500.0410.0660.0360.0000.0000.0070.0250.0150.0200.0110.0330.0240.0450.0291.0000.1150.0130.0240.0250.0270.0270.0100.0280.0130.0320.0050.0230.0090.0270.0090.0430.0290.0370.0340.0180.0160.0210.0260.0340.0290.1460.0110.0240.0260.0000.0000.0190.0420.0000.0000.0000.0000.0000.0000.0000.0010.0660.0390.0270.0000.0410.0160.0230.0090.0350.0060.0300.0370.0420.0350.0090.0000.008
Grid Busbar Temp. Avg. [°C]0.0000.0000.0380.0040.0000.0380.0200.0290.0080.0580.0000.0410.0360.0090.0120.0170.0320.0690.0310.0250.0480.0090.0490.0500.0410.0160.0540.0380.0190.0400.0360.0480.0320.0480.0490.0110.1151.0000.0160.0040.0190.0110.0160.0000.0090.0070.0220.0310.0190.0120.0110.0270.0350.0250.0100.0120.0000.0080.0220.0360.0420.0450.0820.0400.0460.0450.0000.0040.0350.0570.0000.0000.0000.0000.0000.0000.0050.0000.0810.0340.0310.0160.0310.0270.0160.0170.0430.0000.0460.0390.0460.0000.0180.0000.000
Grid InverterPhase1 Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0580.0220.0270.0160.0510.0120.0380.0260.0050.0000.0130.0280.0090.1330.0720.0520.0410.0420.0350.0390.0000.0300.0140.1090.0620.0560.0490.0160.0100.0460.0140.0130.0161.0000.0310.0710.0630.0730.0070.0570.0360.0380.0380.0740.0440.0490.0410.0120.0180.0230.0100.0000.0000.0060.2040.2220.2120.0000.0090.0140.0310.0390.0390.0150.0180.0000.0000.0390.0000.0000.0210.0000.0170.0000.0280.0430.0370.0210.0000.0000.0770.0080.0000.0110.0150.0470.0150.0140.0000.000
Grid Production CosPhi Avg.0.0010.0000.0000.0310.0280.0270.0360.0630.0340.2370.2440.2920.2810.0000.0320.0140.0020.0250.0000.0500.0420.0040.0250.0440.0000.0700.0060.0030.0080.0450.0310.0240.1300.1150.1950.2180.0240.0040.0311.0000.2090.1760.2200.0000.1470.1510.2110.2060.2300.2230.1990.2350.3690.2980.2010.2170.0000.0000.0090.0220.0220.0280.0050.0000.0160.0370.1110.1150.0000.4030.0000.0000.1110.0000.0000.4090.0600.0000.0200.4820.0000.2100.4530.0580.3290.2320.2180.0000.1490.0870.1520.1650.0140.0140.020
Grid Production CurrentPhase1 Avg. [A]0.0000.0000.0290.0220.0070.2360.1040.0970.0330.2000.1110.1710.1370.0070.0480.0000.0000.0180.0000.0810.0820.0560.0530.0720.0170.0070.0000.0060.0040.0590.0390.0460.1720.1460.1360.1430.0250.0190.0710.2091.0000.7210.7700.0040.4980.2390.2310.2670.7070.3490.3520.3120.2580.1780.1440.1300.0160.0220.0630.0490.0550.0450.0110.0000.0000.0240.2030.2040.0850.1900.0160.0000.2020.0020.0100.1570.0620.0200.0020.2880.2240.3600.2890.0000.0910.6770.1440.0000.1850.1090.1160.1210.0290.0000.000
Grid Production CurrentPhase2 Avg. [A]0.0000.0000.0200.0230.0020.2220.1140.0830.0460.1790.1030.1450.1230.0000.0540.0000.0000.0080.0050.0760.0830.0520.0440.0760.0200.0020.0070.0070.0040.0560.0300.0300.1640.1470.1050.1420.0270.0110.0630.1760.7211.0000.7210.0000.4820.2420.2270.2700.6010.3240.3260.2870.2280.1740.1270.1290.0140.0150.0520.0460.0440.0340.0110.0000.0000.0180.1960.1940.0770.1550.0150.0000.1950.0000.0100.1630.0620.0090.0000.2420.2080.3030.2570.0090.0840.5840.1190.0000.1750.1140.0840.1200.0260.0000.000
Grid Production CurrentPhase3 Avg. [A]0.0000.0000.0230.0260.0080.2310.1010.1060.0390.2060.1150.1720.1400.0050.0530.0000.0040.0140.0000.0780.0810.0560.0450.0770.0160.0000.0030.0170.0000.0610.0370.0400.1740.1490.1310.1510.0270.0160.0730.2200.7700.7211.0000.0050.5060.2490.2380.2790.6760.3590.3460.3240.2480.1820.1370.1390.0150.0160.0680.0450.0450.0380.0100.0000.0020.0200.2070.2080.0880.1980.0150.0000.2050.0010.0100.1460.0620.0130.0000.2790.2220.3620.2780.0000.0950.6610.1380.0000.1860.1080.1090.1220.0270.0000.000
Grid Production Frequency Avg. [Hz]0.0000.0110.0000.0050.0000.0030.0000.0000.0000.0000.0100.0000.0060.0000.0000.0000.0000.0000.0080.0000.0070.0000.0000.0000.0000.0000.0000.0110.0050.0000.0000.0000.0000.0000.0000.0000.0100.0000.0070.0000.0040.0000.0051.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0100.0060.0050.0030.0000.0140.0030.0030.0000.0010.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0010.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0050.0000.0000.000
Grid Production PossiblePower Avg. [W]0.0000.0140.0190.0130.0000.2320.0840.0900.0260.1590.0890.1320.1350.0000.0180.0000.0150.0050.0040.0570.0820.0370.0560.0660.0200.0000.0060.0000.0000.0480.0320.0390.1290.1070.0810.1200.0280.0090.0570.1470.4980.4820.5060.0001.0000.2730.3350.2930.6510.2360.2620.2800.1010.1260.0470.0860.0160.0180.0540.0400.0390.0370.0080.0000.0100.0290.1230.1270.0740.1500.0000.0040.1230.0000.0000.1100.0410.0160.0180.1350.3530.3080.1100.0200.0880.6210.0540.0000.1260.0850.0690.1310.0160.0000.000
Grid Production PossiblePower Max. [W]0.0000.0090.0040.0000.0030.0950.1130.0480.0150.1510.1180.1100.1200.0000.0000.0000.0000.0140.0130.0500.0400.0550.0670.0790.0230.0030.0000.0000.0110.0300.0210.0400.1190.1430.0490.1260.0130.0070.0360.1510.2390.2420.2490.0000.2731.0000.2000.2940.2550.7050.1670.2590.1070.1350.0440.1020.0000.0000.0000.0240.0220.0180.0080.0030.0000.0110.0890.0950.0370.1570.0150.0190.0880.0000.0000.0580.0260.0200.0030.1480.0700.2010.1260.0000.0940.2470.0600.0000.1370.1160.0490.1550.0070.0000.000
Grid Production PossiblePower Min. [W]0.0000.0220.0190.0110.0000.0810.0420.1110.0450.1670.0850.1370.2390.0100.0340.0000.0110.0240.0030.0260.0270.0220.0230.0410.0030.0160.0000.0070.0000.0270.0190.0150.1100.0960.1410.2250.0320.0220.0380.2110.2310.2270.2380.0000.3350.2001.0000.2450.2790.1970.5490.2710.1180.1360.0640.1250.0310.0250.0660.0440.0410.0250.0000.0040.0170.0470.1000.0950.0650.1630.0000.0000.0990.0000.0000.0980.0530.0130.0200.1440.1250.2210.1290.0110.2240.2860.0710.0000.1180.0790.1230.1910.0100.0000.000
Grid Production PossiblePower StdDev [W]0.0000.0100.0200.0090.0030.0530.0690.0550.1420.2530.1560.2020.2250.0010.0260.0000.0000.0180.0130.0220.0370.0280.0530.0530.0040.0000.0000.0010.0000.0280.0170.0200.1920.1750.0960.2390.0050.0310.0380.2060.2670.2700.2790.0000.2930.2940.2451.0000.3110.2960.2250.7960.1810.2350.1070.1350.0010.0100.0250.0270.0410.0320.0000.0050.0130.0370.0990.0980.0640.2390.0000.0000.0980.0000.0000.0920.0810.0000.0130.1980.1090.2820.1810.0490.1460.3170.1320.0000.1910.1540.0780.2050.0150.0000.000
Grid Production Power Avg. [W]0.0050.0000.0240.0110.0000.2330.1030.1010.0320.2080.1170.1890.1650.0070.0390.0000.0000.0160.0130.0610.0820.0450.0630.0680.0140.0000.0070.0000.0040.0520.0390.0390.1670.1270.1470.1510.0230.0190.0740.2300.7070.6010.6760.0000.6510.2550.2790.3111.0000.3450.3890.3610.2210.1770.1210.1230.0070.0080.0700.0480.0610.0590.0060.0020.0090.0320.2100.2080.0900.2040.0000.0000.2090.0000.0100.1730.0710.0130.0070.3000.3360.4220.2490.0000.1220.8590.1270.0000.1750.1000.1230.1440.0190.0080.000
Grid Production Power Max. [W]0.0000.0000.0040.0040.0000.0900.1060.0450.0250.1790.1320.1390.1240.0000.0170.0000.0140.0190.0060.0400.0420.0520.0540.0720.0180.0000.0000.0000.0020.0450.0360.0470.1330.1600.0610.1420.0090.0120.0440.2230.3490.3240.3590.0000.2360.7050.1970.2960.3451.0000.2250.3160.1720.1900.0690.1080.0000.0000.0190.0200.0330.0240.0000.0000.0000.0120.1030.1070.0280.1900.0000.0000.1030.0000.0000.0680.0190.0240.0000.1990.0610.2500.2000.0210.0930.3320.0890.0000.1500.1230.0530.1560.0070.0000.000
Grid Production Power Min. [W]0.0010.0000.0100.0000.0000.0980.0710.1250.0310.1620.0760.1400.1920.0050.0440.0080.0000.0200.0000.0310.0300.0270.0130.0230.0000.0040.0050.0000.0000.0310.0120.0190.1010.0930.1620.2030.0270.0110.0490.1990.3520.3260.3460.0050.2620.1670.5490.2250.3890.2251.0000.2750.1760.1420.1480.1400.0250.0120.0590.0410.0460.0350.0130.0000.0160.0320.0910.0910.0600.1650.0000.0000.0910.0000.0060.1370.0940.0000.0210.1990.1130.2700.1900.0050.2050.3800.0970.0000.1150.0670.1350.1680.0240.0130.000
Grid Production Power StdDev [W]0.0000.0190.0170.0110.0000.0540.0640.0600.1360.2620.1180.2420.2630.0000.0330.0000.0000.0140.0180.0200.0390.0320.0480.0430.0060.0000.0000.0000.0000.0280.0170.0170.1870.1450.1060.2550.0090.0270.0410.2350.3120.2870.3240.0000.2800.2590.2710.7960.3610.3160.2751.0000.2290.2430.1440.1760.0060.0100.0430.0380.0390.0370.0000.0090.0080.0380.1530.1540.1080.2570.0260.0000.1520.0210.0290.1020.0770.0000.0140.2280.1400.3060.1970.0830.1710.3660.1640.0000.1830.1270.0810.2130.0120.0000.000
Grid Production ReactivePower Avg. [W]0.0000.0000.0210.0280.0560.0530.0520.0850.0230.4060.1640.5780.4580.0060.0440.0000.0000.0220.0000.0210.0610.0000.0500.0750.0100.0540.0000.0000.0000.0360.0190.0120.2130.1680.3110.2040.0430.0350.0120.3690.2580.2280.2480.0000.1010.1070.1180.1810.2210.1720.1760.2291.0000.5670.4700.4130.0000.0000.0380.0130.0230.0160.0000.0000.0120.0460.1590.1610.2600.6010.0000.0000.1580.0000.0000.1970.0570.0000.0070.6360.1440.2410.7490.1410.4730.2100.5910.0000.2440.1340.2400.1580.0290.0000.034
Grid Production ReactivePower Max. [W]0.0000.0000.0190.0190.0380.0370.0480.1020.0380.3200.1630.4940.3730.0090.0330.0000.0000.0210.0000.0290.0430.0430.0640.0610.0130.0140.0000.0000.0120.0320.0190.0110.1920.1540.2940.1970.0290.0250.0180.2980.1780.1740.1820.0100.1260.1350.1360.2350.1770.1900.1420.2430.5671.0000.5070.4200.0100.0020.0700.0210.0300.0240.0000.0100.0140.0280.1100.1090.2650.5330.0000.0000.1090.0000.0000.1580.0450.0000.0000.4460.1700.2520.4250.1870.3760.1800.4400.0000.2150.1270.2310.1530.0140.0000.014
Grid Production ReactivePower Min. [W]0.0000.0000.0080.0270.0290.0440.0360.1150.0260.2180.0470.4140.2840.0000.0260.0000.0040.0140.0070.0300.0390.0550.0770.0530.0170.0070.0000.0080.0000.0180.0070.0000.1930.0690.3370.1900.0370.0100.0230.2010.1440.1270.1370.0060.0470.0440.0640.1070.1210.0690.1480.1440.4700.5071.0000.4300.0230.0160.0940.0290.0180.0310.0000.0130.0150.0220.0850.0790.2760.4450.0000.0000.0820.0000.0000.1210.1020.0000.0000.3930.1950.1470.3730.1860.3190.1230.4050.0000.2190.0560.2680.1430.0110.0000.012
Grid Production ReactivePower StdDev [W]0.0000.0130.0200.0060.0000.0400.0400.0860.0420.2040.0600.3560.3210.0140.0150.0060.0030.0160.0120.0400.0430.0460.0850.0710.0250.0030.0110.0250.0000.0180.0190.0190.1570.0700.2280.2410.0340.0120.0100.2170.1300.1290.1390.0050.0860.1020.1250.1350.1230.1080.1400.1760.4130.4200.4301.0000.0120.0110.0660.0120.0160.0150.0000.0110.0160.0240.0620.0630.1780.3720.0070.0000.0620.0040.0000.0840.0980.0180.0000.3420.1360.1420.3240.1380.3290.1210.3380.0000.1600.0650.1870.2310.0100.0000.006
Grid Production VoltagePhase1 Avg. [V]0.0000.0000.0030.0090.0060.0000.0000.0160.0000.0000.0000.0080.0000.0000.0130.0000.0000.0230.0000.0000.0000.0000.0030.0000.0110.0070.0000.0000.0000.0000.0040.0000.0080.0040.0140.0130.0180.0000.0000.0000.0160.0140.0150.0030.0160.0000.0310.0010.0070.0000.0250.0060.0000.0100.0230.0121.0000.5560.2520.0000.0070.0000.0000.0000.0000.0130.0000.0000.0350.0110.0070.0000.0000.0120.0030.0000.0100.0000.0000.0060.0400.0100.0090.0110.0000.0080.0000.0000.0030.0090.0110.0000.0000.0000.000
Grid Production VoltagePhase2 Avg. [V]0.0000.0020.0000.0190.0060.0050.0000.0010.0000.0060.0040.0000.0050.0000.0070.0000.0000.0110.0010.0000.0050.0050.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0080.0060.0090.0070.0160.0080.0000.0000.0220.0150.0160.0000.0180.0000.0250.0100.0080.0000.0120.0100.0000.0020.0160.0110.5561.0000.2660.0100.0120.0080.0000.0000.0070.0070.0070.0080.0270.0130.0310.0000.0070.0420.0230.0000.0000.0000.0000.0000.0380.0080.0080.0160.0000.0140.0040.0000.0030.0090.0140.0000.0010.0000.000
Grid Production VoltagePhase3 Avg. [V]0.0000.0000.0000.0000.0000.0270.0260.0510.0000.0360.0060.0570.0320.0000.0110.0000.0000.0160.0130.0250.0230.0570.0650.0560.0280.0090.0070.0050.0050.0000.0000.0020.1010.0270.0920.0480.0210.0220.0060.0090.0630.0520.0680.0140.0540.0000.0660.0250.0700.0190.0590.0430.0380.0700.0940.0660.2520.2661.0000.0160.0060.0010.0000.0180.0110.0320.1030.1010.1950.0790.0000.0000.1020.0000.0000.0060.0020.0060.0000.0140.2100.0270.0060.1020.0000.0690.0730.0000.1090.0250.0810.0370.0060.0000.000
Grid RotorInvPhase1 Temp. Avg. [°C]0.0000.0000.0000.0000.0100.0290.0180.0310.0130.0550.0150.0450.0400.0020.0000.0110.0260.0000.1920.0540.0600.0500.0440.0420.0390.0130.0330.0200.1420.0840.0590.0660.0330.0240.0460.0260.0260.0360.2040.0220.0490.0460.0450.0030.0400.0240.0440.0270.0480.0200.0410.0380.0130.0210.0290.0120.0000.0100.0161.0000.2510.4130.0060.0350.0160.0360.0340.0320.0230.0280.0000.0000.0320.0000.0000.0210.0130.0000.0000.0340.0290.0210.0280.0030.0000.0510.0150.0000.0260.0340.0430.0140.0080.0000.000
Grid RotorInvPhase2 Temp. Avg. [°C]0.0000.0000.0120.0060.0120.0440.0150.0150.0100.0490.0190.0350.0280.0000.0000.0100.0270.0170.2080.0640.0520.0500.0490.0540.0330.0000.0420.0310.1570.0780.0630.0820.0400.0050.0410.0200.0340.0420.2220.0220.0550.0440.0450.0030.0390.0220.0410.0410.0610.0330.0460.0390.0230.0300.0180.0160.0070.0120.0060.2511.0000.3070.0000.0210.0130.0160.0320.0360.0110.0180.0000.0000.0310.0000.0000.0200.0140.0080.0000.0340.0290.0210.0290.0070.0000.0620.0250.0000.0260.0250.0420.0170.0120.0000.000
Grid RotorInvPhase3 Temp. Avg. [°C]0.0000.0000.0050.0000.0070.0310.0160.0150.0080.0370.0140.0370.0240.0000.0020.0190.0320.0140.2140.0380.0600.0430.0470.0420.0460.0000.0490.0190.1550.0840.0500.0580.0370.0220.0440.0190.0290.0450.2120.0280.0450.0340.0380.0000.0370.0180.0250.0320.0590.0240.0350.0370.0160.0240.0310.0150.0000.0080.0010.4130.3071.0000.0100.0280.0000.0280.0230.0230.0130.0280.0000.0000.0230.0000.0000.0140.0040.0000.0000.0410.0340.0170.0330.0040.0000.0590.0230.0020.0280.0330.0420.0210.0070.0000.000
HVTrafo AirOutlet Temp. Avg. [°C]0.0000.0000.0220.0090.0060.0080.0150.0320.0210.0000.0000.0000.0040.0000.0050.0360.0130.0550.0000.0060.0270.0020.0130.0000.0080.0000.0140.0150.0000.0050.0000.0060.0040.0000.0000.0000.1460.0820.0000.0050.0110.0110.0100.0010.0080.0080.0000.0000.0060.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0101.0000.0140.0420.0210.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0050.0000.0530.0000.0270.0000.0000.0000.0100.0070.0000.0000.0000.0000.0000.0000.0120.0000.000
HVTrafo Phase1 Temp. Avg. [°C]0.0000.0000.0220.0000.0000.0000.0000.0090.0000.0230.0230.0020.0220.0000.0220.0330.0330.0270.0140.0100.0190.0050.0000.0000.0250.0080.0500.0480.0250.0210.0430.0460.0110.0000.0100.0000.0110.0400.0090.0000.0000.0000.0000.0000.0000.0030.0040.0050.0020.0000.0000.0090.0000.0100.0130.0110.0000.0000.0180.0350.0210.0280.0141.0000.2260.1720.0000.0000.0630.0330.0000.0000.0000.0020.0000.0100.0000.0000.0360.0000.0630.0150.0120.0090.0180.0000.0070.0000.0000.0000.0000.0000.0150.0000.000
HVTrafo Phase2 Temp. Avg. [°C]0.0000.0000.0260.0000.0000.0120.0010.0160.0110.0140.0030.0150.0140.0000.0130.0270.0400.0500.0190.0130.0200.0000.0090.0050.0120.0440.0240.0330.0230.0180.0190.0320.0000.0000.0230.0070.0240.0460.0140.0160.0000.0000.0020.0030.0100.0000.0170.0130.0090.0000.0160.0080.0120.0140.0150.0160.0000.0070.0110.0160.0130.0000.0420.2261.0000.1380.0040.0030.0480.0390.0000.0000.0040.0000.0000.0130.0110.0100.0720.0000.0520.0190.0000.0000.0290.0060.0040.0000.0000.0000.0170.0000.0110.0000.000
HVTrafo Phase3 Temp. Avg. [°C]0.0000.0000.0060.0000.0000.0000.0120.0150.0070.0450.0020.0440.0650.0110.0110.0100.0290.0510.0140.0000.0260.0000.0150.0000.0300.0310.0460.0260.0220.0400.0520.0280.0060.0230.0420.0330.0260.0450.0310.0370.0240.0180.0200.0000.0290.0110.0470.0370.0320.0120.0320.0380.0460.0280.0220.0240.0130.0070.0320.0360.0160.0280.0210.1720.1381.0000.0050.0000.0570.0690.0000.0000.0040.0000.0000.0310.0170.0000.0400.0320.0680.0450.0340.0000.0640.0310.0240.0000.0070.0170.0310.0270.0000.0000.000
HourCounters Average AlarmActive Avg. [h]0.0000.0470.0120.0040.0570.0000.0000.0000.0000.1430.0950.1370.1190.0000.0190.0000.0060.0110.0100.0500.0680.0810.0600.0510.0250.0310.0000.0000.0070.0090.0000.0000.1390.0960.1080.0950.0000.0000.0390.1110.2030.1960.2070.0000.1230.0890.1000.0990.2100.1030.0910.1530.1590.1100.0850.0620.0000.0070.1030.0340.0320.0230.0000.0000.0040.0051.0000.8990.2340.0080.1420.0710.9770.1340.1780.1360.0220.0180.0000.2020.2370.0000.1910.0750.0000.2150.0980.0000.1510.0780.0950.0770.0140.0000.000
HourCounters Average AmbientOk Avg. [h]0.0000.0480.0070.0050.0500.0000.0000.0000.0000.1350.0890.1330.1120.0000.0100.0000.0060.0110.0090.0490.0700.0760.0570.0480.0230.0220.0000.0000.0000.0100.0000.0000.1360.0990.1020.0910.0000.0040.0390.1150.2040.1940.2080.0000.1270.0950.0950.0980.2080.1070.0910.1540.1610.1090.0790.0630.0000.0080.1010.0320.0360.0230.0000.0000.0030.0000.8991.0000.2230.0090.2290.1720.9170.1370.1490.1400.0250.0190.0000.2010.2340.0000.1900.0700.0030.2130.0950.0000.1470.0810.0890.0710.0000.0000.000
HourCounters Average Gen1 Avg. [h]0.0000.0000.0000.0000.0000.0280.0240.0920.0140.1730.0230.3020.2310.0000.0000.0170.0160.0000.0070.0120.0260.0200.0190.0170.0150.0000.0130.0080.0000.0000.0140.0080.0460.0850.1640.0070.0190.0350.0150.0000.0850.0770.0880.0000.0740.0370.0650.0640.0900.0280.0600.1080.2600.2650.2760.1780.0350.0270.1950.0230.0110.0130.0110.0630.0480.0570.2340.2231.0000.5580.0000.0020.2330.0000.0130.0190.0000.0000.0000.0420.5710.4030.0270.2590.1650.0880.2400.0000.0570.0590.1410.0000.0000.0000.000
HourCounters Average Gen2 Avg. [h]0.0000.0000.0080.0190.0260.0560.0490.1130.0200.3620.1690.5240.4060.0080.0190.0000.0000.0270.0000.0150.0510.0070.0480.0750.0110.0410.0070.0000.0130.0230.0140.0000.1760.1850.3430.1910.0420.0570.0180.4030.1900.1550.1980.0000.1500.1570.1630.2390.2040.1900.1650.2570.6010.5330.4450.3720.0110.0130.0790.0280.0180.0280.0000.0330.0390.0690.0080.0090.5581.0000.0000.0000.0110.0000.0030.1920.0480.0000.0060.6100.2710.5330.5460.0980.4840.2120.4360.0000.2040.1460.2710.1420.0220.0000.008
HourCounters Average GridOk Avg. [h]0.0000.1710.0000.0000.0000.0000.0000.0000.0000.0050.0000.0160.0270.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0070.0000.0150.0000.0000.0000.0000.0160.0150.0150.0000.0000.0150.0000.0000.0000.0000.0000.0260.0000.0000.0000.0070.0070.0310.0000.0000.0000.0000.0000.0000.0000.0000.1420.2290.0000.0001.0000.5910.2220.4720.5130.0220.0000.0000.0000.0260.0000.0000.0120.0000.0000.0160.0000.0000.0000.0010.0000.0000.0000.0000.000
HourCounters Average GridOn Avg. [h]0.0000.3370.0000.0000.0000.0000.0000.0270.0000.0000.0000.0000.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0710.1720.0020.0000.5911.0000.1190.3350.3370.0400.0000.0000.0000.0170.0040.0000.0300.0000.0000.0000.0010.0000.0000.0000.0000.0000.0110.0000.000
HourCounters Average Run Avg. [h]0.0000.0140.0140.0040.0570.0000.0000.0000.0000.1390.0920.1360.1160.0000.0160.0000.0060.0110.0090.0490.0680.0800.0590.0510.0240.0310.0000.0000.0070.0090.0000.0000.1380.0960.1070.0950.0000.0000.0390.1110.2020.1950.2050.0000.1230.0880.0990.0980.2090.1030.0910.1520.1580.1090.0820.0620.0000.0070.1020.0320.0310.0230.0000.0000.0040.0040.9770.9170.2330.0110.2220.1191.0000.0800.2420.1380.0210.0180.0000.2010.2350.0000.1870.0740.0000.2140.0950.0000.1500.0770.0940.0760.0110.0000.000
HourCounters Average ServiceOn Avg. [h]0.0000.2260.0000.0000.0000.0000.0000.0070.0000.0230.0000.0120.0290.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0140.0000.0110.0000.0000.0000.0000.0020.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0210.0000.0000.0000.0040.0120.0420.0000.0000.0000.0000.0000.0020.0000.0000.1340.1370.0000.0000.4720.3350.0801.0000.2260.0000.0000.0030.0000.0200.0000.0000.0190.0000.0000.0030.0050.0000.0000.0100.0000.0000.0000.0000.000
HourCounters Average TurbineOk Avg. [h]0.0000.0450.0000.0000.0000.0000.0000.0000.0000.0160.0000.0170.0180.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0150.0000.0000.0160.0000.0000.0000.0000.0100.0100.0100.0000.0000.0000.0000.0000.0100.0000.0060.0290.0000.0000.0000.0000.0030.0230.0000.0000.0000.0000.0000.0000.0000.0000.1780.1490.0130.0030.5130.3370.2420.2261.0000.0150.0000.0000.0000.0190.0000.0000.0070.0000.0000.0110.0000.0000.0000.0060.0000.0000.0000.0000.000
HourCounters Average WindOk Avg. [h]0.0000.0050.0000.0190.0030.0380.0460.0500.0200.1040.1750.1680.1340.0000.0240.0070.0100.0170.0000.0450.0460.0000.0000.0140.0010.0870.0000.0060.0130.0410.0160.0170.0410.0380.1480.0710.0000.0000.0210.4090.1570.1630.1460.0000.1100.0580.0980.0920.1730.0680.1370.1020.1970.1580.1210.0840.0000.0000.0060.0210.0200.0140.0000.0100.0130.0310.1360.1400.0190.1920.0220.0400.1380.0000.0151.0000.0230.0100.0080.3080.0180.1490.2510.0550.1760.1800.0980.0000.0600.0120.1190.0340.0000.0000.000
HourCounters Average Yaw Avg. [h]0.0000.0000.0000.0290.0220.0150.0130.0060.0510.0770.0260.0410.0930.0000.0120.0000.0000.0100.0050.0110.0000.0050.0000.0000.0000.0160.0000.0060.0000.0110.0130.0000.0420.0250.0270.1040.0000.0050.0000.0600.0620.0620.0620.0000.0410.0260.0530.0810.0710.0190.0940.0770.0570.0450.1020.0980.0100.0000.0020.0130.0140.0040.0050.0000.0110.0170.0220.0250.0000.0480.0000.0000.0210.0000.0000.0231.0000.0120.0150.0700.0000.0550.0720.0070.0570.0700.0570.0000.0390.0290.0220.0730.0090.0000.000
Hydraulic Oil Temp. Avg. [°C]0.0000.0000.0050.0000.0000.0000.0000.0000.0020.0000.0130.0000.0150.0000.0000.0410.0000.0000.0000.0000.0000.0120.0050.0000.0000.0150.0000.0000.0040.0000.0150.0000.0000.0000.0090.0040.0010.0000.0170.0000.0200.0090.0130.0000.0160.0200.0130.0000.0130.0240.0000.0000.0000.0000.0000.0180.0000.0000.0060.0000.0080.0000.0000.0000.0100.0000.0180.0190.0000.0000.0000.0000.0180.0030.0000.0100.0121.0000.0000.0000.0030.0000.0000.0030.0000.0130.0000.0000.0000.0080.0160.0160.0000.0080.000
Nacelle Temp. Avg. [°C]0.0000.0000.1170.0100.0130.0000.0130.0110.0030.0170.0170.0070.0030.0070.0150.0470.0000.0780.0020.0000.0040.0100.0040.0020.0150.0490.0120.0170.0250.0080.0290.0200.0000.0000.0060.0000.0660.0810.0000.0200.0020.0000.0000.0040.0180.0030.0200.0130.0070.0000.0210.0140.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0530.0360.0720.0400.0000.0000.0000.0060.0000.0000.0000.0000.0000.0080.0150.0001.0000.0000.0060.0150.0000.0160.0030.0130.0040.0000.0000.0000.0110.0000.0730.0000.003
Production LatestAverage Active Power Gen 0 Avg. [W]0.0000.0080.0230.0360.0510.0550.0540.0640.0110.2910.2090.4230.3080.0000.0330.0150.0080.0350.0020.0510.0800.0230.0750.1030.0280.0530.0000.0080.0170.0480.0360.0220.2300.1680.3480.2200.0390.0340.0280.4820.2880.2420.2790.0010.1350.1480.1440.1980.3000.1990.1990.2280.6360.4460.3930.3420.0060.0000.0140.0340.0340.0410.0000.0000.0000.0320.2020.2010.0420.6100.0260.0170.2010.0200.0190.3080.0700.0000.0001.0000.0410.1770.7880.0340.4080.3390.4130.0000.2630.1370.2710.1710.0240.0000.030
Production LatestAverage Active Power Gen 1 Avg. [W]0.0000.0000.0160.0070.0030.1220.0370.0830.0170.1060.0020.1890.1380.0000.0000.0170.0040.0000.0130.0610.0910.0520.0610.0530.0370.0000.0000.0160.0000.0170.0000.0000.0550.0160.1360.0100.0270.0310.0430.0000.2240.2080.2220.0000.3530.0700.1250.1090.3360.0610.1130.1400.1440.1700.1950.1360.0400.0380.2100.0290.0290.0340.0270.0630.0520.0680.2370.2340.5710.2710.0000.0040.2350.0000.0000.0180.0000.0030.0060.0411.0000.0390.0250.1930.0630.3890.1580.0000.0490.0000.1170.0290.0000.0000.000
Production LatestAverage Active Power Gen 2 Avg. [W]0.0000.0000.0000.0090.0140.1020.0600.0820.0270.2640.0970.2900.2660.0120.0340.0000.0100.0310.0000.0100.0000.0040.0000.0190.0050.0080.0000.0120.0000.0110.0000.0000.1080.1650.1400.1510.0000.0160.0370.2100.3600.3030.3620.0000.3080.2010.2210.2820.4220.2500.2700.3060.2410.2520.1470.1420.0100.0080.0270.0210.0210.0170.0000.0150.0190.0450.0000.0000.4030.5330.0000.0000.0000.0000.0000.1490.0550.0000.0150.1770.0391.0000.1390.0520.2790.4510.1550.0000.1270.1230.1150.1110.0170.0060.000
Production LatestAverage Reactive Power Gen 0 Avg. [var]0.0000.0170.0170.0280.0620.0520.0510.0570.0100.3140.2200.4040.3140.0070.0400.0160.0110.0300.0000.0410.0850.0170.0720.1050.0270.0670.0000.0000.0150.0490.0360.0260.2610.1900.3370.2460.0410.0310.0210.4530.2890.2570.2780.0000.1100.1260.1290.1810.2490.2000.1900.1970.7490.4250.3730.3240.0090.0080.0060.0280.0290.0330.0000.0120.0000.0340.1910.1900.0270.5460.0120.0300.1870.0190.0070.2510.0720.0000.0000.7880.0250.1391.0000.0450.3870.2450.5040.0000.2960.1560.2640.1960.0260.0000.042
Production LatestAverage Reactive Power Gen 1 Avg. [var]0.0000.0000.0090.0100.0170.0000.0080.0310.0000.1140.0360.1850.1510.0000.0000.0340.0000.0050.0240.0060.0000.0260.0260.0270.0000.0690.0060.0000.0000.0290.0380.0260.0500.0130.0380.0080.0160.0270.0000.0580.0000.0090.0000.0000.0200.0000.0110.0490.0000.0210.0050.0830.1410.1870.1860.1380.0110.0160.1020.0030.0070.0040.0000.0090.0000.0000.0750.0700.2590.0980.0000.0000.0740.0000.0000.0550.0070.0030.0160.0340.1930.0520.0451.0000.0460.0000.7110.0000.0390.0320.0380.0070.0150.0000.000
Production LatestAverage Reactive Power Gen 2 Avg. [var]0.0160.0000.0000.0080.0100.0140.0200.0710.0280.2470.0680.4310.4730.0000.0160.0080.0000.0220.0010.0130.0160.0290.0000.0000.0000.0460.0020.0110.0000.0060.0000.0000.0810.1030.2110.2790.0230.0160.0000.3290.0910.0840.0950.0070.0880.0940.2240.1460.1220.0930.2050.1710.4730.3760.3190.3290.0000.0000.0000.0000.0000.0000.0100.0180.0290.0640.0000.0030.1650.4840.0000.0000.0000.0000.0000.1760.0570.0000.0030.4080.0630.2790.3870.0461.0000.1250.4080.0000.1000.0720.1530.2090.0210.0060.030
Production LatestAverage Total Active Power Avg. [W]0.0060.0000.0270.0130.0020.2290.0970.1000.0300.2190.1230.1980.1700.0030.0390.0000.0000.0230.0150.0650.0840.0570.0670.0760.0230.0000.0000.0000.0050.0500.0340.0340.1790.1330.1620.1600.0090.0170.0770.2320.6770.5840.6610.0000.6210.2470.2860.3170.8590.3320.3800.3660.2100.1800.1230.1210.0080.0140.0690.0510.0620.0590.0070.0000.0060.0310.2150.2130.0880.2120.0160.0000.2140.0030.0110.1800.0700.0130.0130.3390.3890.4510.2450.0000.1251.0000.1240.0000.1910.1030.1350.1470.0220.0080.000
Production LatestAverage Total Reactive Power Avg. [var]0.0000.0000.0170.0020.0210.0300.0370.0780.0120.2930.0920.4290.3310.0040.0190.0230.0000.0110.0200.0260.0410.0190.0600.0790.0140.0110.0030.0000.0100.0000.0000.0000.1810.1070.2340.1380.0350.0430.0080.2180.1440.1190.1380.0000.0540.0600.0710.1320.1270.0890.0970.1640.5910.4400.4050.3380.0000.0040.0730.0150.0250.0230.0000.0070.0040.0240.0980.0950.2400.4360.0000.0010.0950.0050.0000.0980.0570.0000.0040.4130.1580.1550.5040.7110.4080.1241.0000.0000.1900.1240.1890.1080.0000.0000.013
Reactive power generator 0,Total accumulated [var]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.000
Rotor RPM Avg. [RPM]0.0000.0000.0100.0160.0350.1290.0630.0860.0370.2040.0660.1940.1480.0000.0170.0040.0080.0030.0000.0920.1170.1380.1940.1980.0940.0300.0200.0430.0150.0570.0410.0400.7380.2900.4070.4230.0300.0460.0110.1490.1850.1750.1860.0000.1260.1370.1180.1910.1750.1500.1150.1830.2440.2150.2190.1600.0030.0030.1090.0260.0260.0280.0000.0000.0000.0070.1510.1470.0570.2040.0000.0000.1500.0000.0000.0600.0390.0000.0000.2630.0490.1270.2960.0390.1000.1910.1900.0001.0000.2580.3850.3550.0100.0000.012
Rotor RPM Max. [RPM]0.0000.0000.0000.0000.0580.0690.0710.0400.0250.1530.1850.1170.1080.0000.0000.0000.0000.0200.0050.0520.0580.0670.0510.1160.0380.0280.0230.0100.0230.0150.0180.0000.3230.7210.1000.2200.0370.0390.0150.0870.1090.1140.1080.0000.0850.1160.0790.1540.1000.1230.0670.1270.1340.1270.0560.0650.0090.0090.0250.0340.0250.0330.0000.0000.0000.0170.0780.0810.0590.1460.0010.0000.0770.0100.0060.0120.0290.0080.0000.1370.0000.1230.1560.0320.0720.1030.1240.0000.2581.0000.1030.1680.0110.0100.000
Rotor RPM Min. [RPM]0.0000.0000.0200.0060.0200.0850.0370.1310.0070.1400.0330.2490.1470.0050.0090.0080.0000.0030.0140.0810.1030.0870.1390.1300.0720.0310.0390.0300.0250.0640.0630.0510.3550.0980.7740.2400.0420.0460.0470.1520.1160.0840.1090.0000.0690.0490.1230.0780.1230.0530.1350.0810.2400.2310.2680.1870.0110.0140.0810.0430.0420.0420.0000.0000.0170.0310.0950.0890.1410.2710.0000.0000.0940.0000.0000.1190.0220.0160.0110.2710.1170.1150.2640.0380.1530.1350.1890.0000.3850.1031.0000.1900.0000.0000.022
Rotor RPM StdDev [RPM]0.0000.0110.0000.0150.0220.0610.0260.0570.0750.1460.0470.1550.2770.0120.0210.0000.0240.0230.0060.0570.0490.0720.1010.0810.0340.0110.0000.0000.0000.0260.0110.0120.3630.1980.2120.6620.0350.0000.0150.1650.1210.1200.1220.0050.1310.1550.1910.2050.1440.1560.1680.2130.1580.1530.1430.2310.0000.0000.0370.0140.0170.0210.0000.0000.0000.0270.0770.0710.0000.1420.0000.0000.0760.0000.0000.0340.0730.0160.0000.1710.0290.1110.1960.0070.2090.1470.1080.0000.3550.1680.1901.0000.0150.0130.011
Spinner Temp. Avg. [°C]0.0000.0120.0490.0030.0150.0050.0020.0070.0120.0110.0020.0080.0180.0000.0500.0270.0000.0140.0000.0070.0000.0000.0070.0000.0040.0360.0000.0090.0000.0090.0090.0220.0000.0230.0000.0140.0090.0180.0140.0140.0290.0260.0270.0000.0160.0070.0100.0150.0190.0070.0240.0120.0290.0140.0110.0100.0000.0010.0060.0080.0120.0070.0120.0150.0110.0000.0140.0000.0000.0220.0000.0110.0110.0000.0000.0000.0090.0000.0730.0240.0000.0170.0260.0150.0210.0220.0000.0000.0100.0110.0000.0151.0000.0000.000
Total Active power [W]0.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0030.0120.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0060.0000.0000.0060.0080.0000.0000.0000.0100.0000.0130.0001.0000.000
Total reactive power [var]0.0000.0000.0000.0000.0200.0000.0000.0000.0000.0100.0000.0180.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0080.0000.0000.0000.0090.0000.0320.0160.0080.0000.0000.0200.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0340.0140.0120.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0030.0300.0000.0000.0420.0000.0300.0000.0130.0000.0120.0000.0220.0110.0000.0001.000

Missing values

2025-05-15T14:32:02.680237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-15T14:32:03.531307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
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12020-01-01 00:10:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
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32020-01-01 00:30:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
42020-01-01 00:40:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
52020-01-01 00:50:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
62020-01-01 01:00:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
72020-01-01 01:10:0000000000001000100000100000000000000011100000000000000000000000000000000000100001001000100000000000000000000000000000000000000000
82020-01-01 01:20:0000000000000000110000100001000010000000000000000000000000000000000000000000100000000000100000000010000000000000000000000000000000
92020-01-01 01:30:0000100011001000010011000011000010000001000000000000000000000000000000000000100010000010000000000000000000000000000000000000000000
TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
261982020-06-30 22:20:0000000000100000000000000000000000000000000000000000000000000000000000000000000000000000001000000010000000000000000000000000000000
261992020-06-30 22:30:0000000000101000100000000000000000000001100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
262002020-06-30 22:40:0000000000000000000000000000000010000000000000000000000010000000000000000000000000001000000000000000000000000000000000000000000000
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